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How to Implement Infor ERP in Half the Time?

Jerome Josephraj — Thu, 16 Apr 2026 14:32:04 GMT

Requirements buried deep in documentation only surface during UAT. SMEs explain the same processes multiple times to different teams. Decisions get revisited because context is lost between phases. Test scripts take months to prepare and weeks to execute manually. Training gets diluted as it passes through layers before it reaches the end user.

We’ve seen what happens when a 12-month plan turns into 18.
Momentum fades. Priorities shift. Teams disengage. And by the time you go live, parts of the business have already outgrown the original design.

It’s not the ERP system that creates the problem.
It’s the way implementations are executed — sequential, manual, and heavily dependent on a few key people.

And that’s exactly what’s changing.

Here’s what happens when AI is embedded across every phase of an ERP implementation:

→ Requirements: From fragmented input to full visibility

Traditional requirements gathering is slow and incomplete by design. It depends on workshops, documentation reviews, and human recall — which means important details are often missed until much later.

AI changes this completely. It can ingest and analyze vast amounts of documentation at once: process descriptions, legacy system data, industry templates, and edge cases. Instead of discovering gaps during testing, teams identify them upfront.

The result isn’t just speed — it’s better accuracy from day one, and far less rework downstream.

→ Configuration: From bottlenecks to scalable execution

Configuration is often constrained by a small number of senior consultants who understand both the system and the business context. This creates a natural bottleneck.

With AI support, configuration becomes more accessible. Requirements can be translated into system setups through guided, natural-language interactions. Junior consultants can execute with greater confidence, while senior experts focus on validating decisions, not performing repetitive setup tasks.

This doesn’t reduce quality — it redistributes effort to where it matters most.

→ Testing: From manual effort to continuous validation

Testing is one of the most time-consuming phases of any ERP project. Writing test scripts, executing them manually, documenting results — it’s slow, repetitive, and prone to human error.

AI enables a shift from periodic, manual testing to continuous, automated validation. Test scenarios can be generated based on requirements and system configurations, executed at scale, and re-run instantly after changes or updates.

What used to take weeks can happen overnight.
And more importantly, issues are caught earlier — when they’re easier to fix.

→ Training: From static materials to living knowledge

Traditional training approaches rely on static documentation and scheduled sessions, often created long before go-live. By the time users are trained, the system has already evolved.

AI allows training to become dynamic and contextual. Users receive role-specific guidance based on what they’re doing in the system, not what was documented months earlier. Content stays up to date automatically, and support doesn’t end after go-live.

Adoption improves because learning becomes continuous — not a one-time event.

→ Support: From reset to continuity

One of the biggest inefficiencies in ERP projects happens after go-live. Support teams often start from scratch, without full visibility into the decisions, configurations, and trade-offs made during implementation.

AI changes that by carrying context forward. Every requirement, decision, and configuration becomes part of an accessible knowledge layer. When issues arise, they’re resolved faster because the system “remembers” how and why things were built.

This reduces dependency on specific individuals and creates a more resilient support model.

DOWLOAD FULL GUIDE: FROM MONTHS TO WEEKS:INFOR ERP GUIDE

18 months becomes 9. Not by cutting corners — but by removing the friction that slows everything down.

So what actually changes when AI is embedded across the ERP implementation lifecycle?

The steps don’t disappear: requirements are still gathered, systems are still configured, testing still happens, and users still need training. But the way those steps are executed fundamentally changes.

Work that was once manual becomes automated.
Work that once depended on memory becomes data-driven.

Shorter implementations mean less exposure to changing business conditions. They keep stakeholders engaged, reduce the risk of team turnover, and allow organizations to realize value sooner. In many cases, moving faster is actually the safer path.

ERP implementations don’t have to be long, exhausting transformations.

With AI embedded across the lifecycle, they become more predictable, more efficient, and far less dependent on bottlenecks.

The question is no longer whether ERP projects can move faster.
It’s whether there’s still a reason not to.

Want to Go Deeper?

We’ve put together a practical guide to faster Infor ERP implementation — outlining how each phase can be accelerated without compromising quality, where traditional bottlenecks can be eliminated, and how teams can start executing differently today.

Download the full guide below.

DOWLOAD FULL GUIDE: FROM MONTHS TO WEEKS:INFOR ERP GUIDE

18 months becomes 9. Not by cutting corners — but by removing the friction that slows everything down.

Will AI Replace ERP Consultants?

Jerome Josephraj — Thu, 02 Apr 2026 15:03:14 GMT

ERP projects have a dirty secret. They take too long, cost too much, and burn out the best people in the room. We've normalised project timelines measured in years, training programmes that nobody follows, and support teams who inherit a system they don't understand. And yet, the industry has largely continued this way — because that's how it's always been done.

AI is about to make that excuse disappear.

But before we get into what AI can do, it is important to consider what it actually means for the people who build, deliver, and run ERP systems — because the conversation is far more nuanced than the headlines suggest. The question is not whether AI will change ERP consulting. It will. The question is whether you will be the person wielding it, or the person replaced by it.

Phase 1: Requirements — From Months of Analysis to Minutes

Consider what a requirements phase actually involves. Consultants wade through hundreds of documents — Word files, spreadsheets, PDFs, meeting notes, process maps — often spread across multiple stakeholders who do not agree on what they want. It takes weeks just to read everything, let alone synthesise it into a coherent requirements matrix.

AI agents can now ingest all of that in minutes. Feed them the documents, point them at the company's public-facing information, and they will produce a structured requirements analysis that would have taken a senior consultant weeks to draft.

Implementations that used to begin with a month of discovery work are now starting from an AI-generated baseline — one that consultants then pressure-test, challenge, and validate. The output is not perfect without human oversight. It does not need to be. It simply needs to be good enough that your expert can focus on what actually requires expertise: judgement, relationships, and domain-specific decisions that no model can replicate.

WHAT THIS MEANS FOR YOUR ROLE

If your role is analysing documents and producing requirements matrices, AI now performs a first pass in minutes, not weeks. Your job shifts from extraction to validation and expert judgement.

This is a multiplier, not a replacement. Firms that adopt this will bid for more projects and win more of them. Consultants who master it will be in higher demand, not lower.

The firms that embrace this will be able to take on more projects simultaneously. The ones that do not will find themselves priced out by competitors who can deliver faster at lower cost.

NEW GUIDE: THE ERP AI
OPERATOR PLAYBOOK

How AI is reshaping every phase of ERP delivery,
and what you must master to stay ahead.

Phase 2: Configuration — Natural Language Meets Complex Systems

Configuration is where ERP expertise truly lives. Knowing which settings to change, in which order, with what downstream consequences — this is hard-won knowledge that takes years to develop. It is also, paradoxically, one of the most time-consuming and mechanical parts of any implementation.

The emerging approach is to let consultants describe what they want in plain language, and have AI translate that into the specific configuration steps, API calls, and system changes required. Rather than manually hunting through menus to find the right approval workflow settings, a consultant can simply describe the business rule and let the agent map the path.

However — and this is critical — the agent does not execute. It proposes. A human with deep product knowledge still needs to review every step, because a misconfigured ERP does not just cause a bug. It can affect financial controls, supply chain flows, and compliance across an entire organisation.

WHAT THIS MEANS FOR YOUR ROLE

If your value is in navigating menus and finding the right API, that part is being automated. But if your value is in knowing whether a configuration change is safe and what it might break downstream, that expertise becomes more critical, not less.

AI removes the mechanical hunt. It does not replace the judgement of someone who truly understands the system.

Phase 3: Testing — The End of
Script-Writing Drudgery

Testing is perhaps the most universally disliked phase of any ERP project. Manual test scripts, regression cycles, and the constant fear that a go-live will break something nobody thought to check. It is slow, repetitive, and deeply dependent on people who also need to keep the business running.

AI-powered test agents change this dynamic significantly. Rather than writing scripts from scratch, a tester simply demonstrates a business process — the agent observes, learns, and automates it. Those scripts can then be run at will: before go-live, after every system update, on a regular schedule. The validation that used to take months of manual cycles can now happen continuously, in the background.

WHAT THIS MEANS FOR YOUR ROLE

If your role is following a spreadsheet of test steps and clicking through screens, that specific task is automatable and will be replaced.

If your role is defining what needs to be tested, understanding which business scenarios matter, and interpreting whether a failure is critical or a known quirk, your role has become significantly more strategic.

AI removes the drudgery of execution. It cannot replace the thinking required to define what good looks like.

Phase 4: Training — A Paradigm Shift, Not an Upgrade

Traditional ERP training is one of the biggest sources of go-live failure. The train-the-trainer model creates a game of telephone — information degrades at every handoff. PDF manuals gather dust. Language and cultural barriers make consistent delivery nearly impossible across global rollouts.

The AI-driven alternative starts from a completely different premise: take what was validated in testing, and use it directly as the basis for training. The same process flows that were proven to work become the source material for automatically generated training content — available in the user's own language, accessible on demand, and tied to assessments that actually verify comprehension rather than just attendance.

Perhaps the most significant shift is what happens after the training is done. Rather than leaving users to work things out once they are in the system, AI can now act as a persistent digital assistant — one that understands the context of exactly where a user is in the application, recognises when they are struggling, and surfaces the right guidance with a single click. Not a generic help article. Not a support ticket. The precise answer, in the moment it is needed. That kind of embedded, context-aware support was not possible before AI — and it fundamentally changes what “going live” actually means for end users.

WHAT THIS MEANS FOR YOUR ROLE

If your primary role is producing training materials and documentation from scratch — working with subject-matter experts to write manuals, record videos, and maintain content — this is a genuine displacement.

For everyone else — implementation leads, project managers, and SMEs — this removes one of the most time-consuming and error-prone phases of the project. The expertise required to define the processes does not go away. Only the burden of documenting and maintaining them does.

Phase 5: Support — Institutional Memory, Finally Preserved

Here is a pattern every ERP consultant knows. You spend months — sometimes years — building deep knowledge of a system: the decisions made, the workarounds implemented, the reasons behind unusual configurations. Then the project ends, the team disperses, and the support team inherits a system they have never seen before with documentation that was never quite finished.

AI support agents are beginning to solve this problem in a fundamentally different way. Rather than treating support as a separate function that starts from scratch post-go-live, the emerging model is to build the support agent from the knowledge accumulated across every project phase — requirements, configuration rationale, test results, training content. From day one, the support agent knows why the system was built the way it was, not just what it does.

WHAT THIS MEANS FOR YOUR ROLE

If your role is primarily Tier-1 query routing — answering the same questions repeatedly and escalating to SMEs — that function is automatable.

What is not automatable: spotting a systemic issue beneath a pattern of tickets, managing the relationship dynamics that keep clients feeling genuinely supported, and making judgement calls on edge cases the AI has not seen before.

The support function does not disappear — it moves up the value chain.

So, Will AI Replace ERP Consultants?

Some roles, yes. If your value is in executing repetitive tasks — following scripts, routing queries, producing documentation — the automation wave will reach you. That is not a prediction. It is already happening.

However, ERP implementation is not fundamentally a task-execution problem. It is a change management, decision-making, and domain expertise problem. The reason ERP projects fail is not because people could not click through menus fast enough. It is because the human complexity of changing how an organisation works is genuinely hard.

AI accelerates the mechanical parts of implementation. It does not replace the judgement, relationships, and hard-won knowledge that make implementations actually succeed. If anything, it raises the premium on genuine expertise — because when AI handles the drudgery, the only thing left that justifies a consultant's fees is the insight they bring that the system cannot.

The consultants who thrive in the next five years will be the ones who learn to operate AI agents the way a skilled surgeon operates advanced equipment — faster, more precise, capable of things that were previously impossible. The ones who resist will simply become expensive.

The industrial revolution did not eliminate farming. It eliminated the farmer who refused to use the tractor.

Want to Go Deeper?

We have compiled a practical guide to AI-augmented ERP delivery — covering how each phase is changing, what skills remain irreplaceable, and how implementation teams can begin the transition now.

Download the full guide below.

THE ERP AI
OPERATOR PLAYBOOK

How AI is reshaping every phase of ERP delivery,
and what you must master to stay ahead.

ERP Test Automation Best Practice: Scenario Independence

Jerome Josephraj — Wed, 05 Nov 2025 06:52:36 GMT

Why Scenario Independence Is the Cornerstone of Scalable Test Automation

Summary
Problem: As ERP test automation scales to hundreds or thousands of scenarios, scenario interdependencies create fragile, hard-to-maintain test suites where small changes trigger widespread failures.
Solution: Keep every scenario completely independent — handling its own setup, configuration, execution, validation, and cleanup — while using Infomind’s hooks for shared setup logic. This ensures scalability, stability, and maintainability in complex ERP environments.

1. The Real-World ERP Automation Problem

When you automate tests for a large ERP, you quickly face the temptation to build dependencies between scenarios. For example:

Scenario 10 → Scenario 100 → Scenario 150
 ↓
 Scenario 275 → Scenario 400

Initially, it might seem efficient to “reuse” earlier test outcomes. But as the suite grows to 1000+ scenarios, this web of dependencies becomes a serious liability.

What goes wrong:

A minor change in Scenario 10 could break Scenario 275 or 400
Execution order becomes critical and hard to manage
Circular dependencies creep in over time
Debugging turns into a guessing game
Maintenance cost skyrockets

Bottom line: Scenario dependencies are the hidden time bomb of test automation — especially in ERP systems with complex business flows.

2. The Right Way — Scenario Independence

Each scenario must stand completely on its own.
That means it performs the full workflow independently — from setup to cleanup.

A good independent scenario typically looks like this:

Scenario 10 Scenario 100 Scenario 150 Scenario 275
├─ Data setup ├─ Data setup ├─ Data setup ├─ Data setup
├─ Config setup ├─ Config setup ├─ Config setup ├─ Config setup
├─ Perform test ├─ Perform test ├─ Perform test ├─ Perform test
├─ Validate ├─ Validate ├─ Validate ├─ Validate
└─ Cleanup └─ Cleanup └ ─ Cleanup └─ Cleanup

Advantages:

Predictable and reliable execution
No dependency on previous scenarios
Easy to debug or re-run in isolation
Ideal for parallel or distributed execution
Far lower maintenance effort over time

3. Reusability Without Dependencies — The Infomind Hooks

A common challenge is when multiple scenarios require the same data setup or configuration; for example, setting up company parameters, currencies, or user roles.
Repeating that setup in every scenario is inefficient. But linking scenarios (to reuse it) brings back the same dependency issue.

Infomind solves this elegantly using hooks.

 ┌────────────────────────────┐
 │ HOOKS Layer                │
 │ - Data setup before all    │
 │ - Cleanup after all        │
 │ - Group-level setup        │
 └────────────────────────────┘
 │ │ │ │
 ▼ ▼ ▼ ▼
 Scenario10 Scenario100 Scenario150 Scenario275

Watch this short video to see how Infomind’s hooks handle setup and cleanup effortlessly; keeping your test scenarios independent and maintainable

Hooks let you:

Run a setup once before all or selected scenarios
Automatically clean up afterward
Reuse common configurations safely

Result: You gain efficiency without ever creating inter-scenario dependencies.

4. The Big Question — Testing Long ERP Processes

End-to-end ERP processes such as:

Customer places an order for items not in stock → ERP triggers purchase → goods received → order delivered → customer invoiced → payment posted

…often tempt teams to chain scenarios together for “process continuity.”

But that reintroduces dependencies and all their side effects.

At Infomind, we’re building a new innovation that lets you test long-running, cross-module ERP processes without compromising scenario independence.
You’ll be able to maintain modularity while still validating the full process flow from start to finish.

(More details coming soon — watch this space.)

5. Summary Visual — The Evolution of Maturity

Stage	Approach	Description	Outcome
1	Scenario chaining	Scenarios depend on one another	Brittle, unscalable
2	Independent scenarios	Each scenario self-contained	Stable, maintainable
3	Independent + hooks	Reusable setup without dependency	Efficient and consistent
4	Independent + process orchestration (Infomind innovation)	End-to-end flow coverage	Long-process ready and future-proof

Final Takeaway

Avoid the dependency trap.
Independent scenarios may take a little more thought up front, but they pay back massively in stability, scalability, and confidence.

With Infomind’s hooks and upcoming process orchestration capabilities, you get the best of both worlds:

Reusability without fragility
Speed without chaos
Innovation without compromise

Why Wipro Partnered with Infomind.ai?

Jerome Josephraj — Tue, 14 Oct 2025 10:05:54 GMT

Why Wipro Partnered with Infomind.ai: Accelerating ERP Transformation Through Intelligent Automation

Enterprise ERP programs continue to face persistent challenges; long testing cycles, inconsistent user training, and increasing risk, cost, and time during INFOR ERP rollouts or business process changes. As organizations pursue digital transformation at scale, system integrators are under growing pressure to deliver faster, more reliable, and cost-effective ERP outcomes.

Wipro, a global leader in consulting and technology services, partnered with Infomind.ai to address this exact need. The partnership is built on a shared vision: to use AI to accelerate ERP transformation through intelligent automation and ensure every business process is validated, optimized, and understood.

Driving ERP Efficiency Through Intelligent Process Automation

At the heart of the collaboration are two of Infomind.ai’s flagship AI-powered platforms:

Intelligent Process Tester (IPT) — a no-code, AI-driven testing platform that automates business process validation for ERP systems.
Intelligent Training Academy (ITA) — a platform that automatically converts test scripts into structured training videos and courses using AI, in just a few clicks, and in over 100 languages, simplifying end-user enablement.

By combining these innovations with Wipro’s deep ERP expertise, global reach, and delivery excellence, the partnership enables enterprises to achieve measurable transformation and faster value realization.

Why Wipro Chose Infomind.ai

Wipro selected Infomind.ai after identifying clear strategic and operational advantages:

AI-led innovation alignment: Infomind.ai’s no-code and AI-based automation approach complements Wipro’s ERP modernization strategy.
Scalability and speed: The AI-platform reduces testing and training effort by more than 50%, accelerating project timelines and improving predictability.
Measurable outcomes: Clients benefit from improved quality assurance, faster go-lives, and enhanced user adoption.
Shared vision: Both organizations are committed to redefining ERP delivery through AI-driven intelligent automation.

Delivering Tangible Results for Enterprise Clients

Together, Wipro and Infomind.ai are helping enterprise clients achieve:

Continuous process validation across ERP modules.
Faster and more accurate testing cycles through AI-based automation.
Automated, easy-to-consume training materials for business users.
Reduced project risk and total cost of ownership.

This partnership empowers ERP teams to move beyond traditional testing and training methods, creating a new standard for efficiency, scalability, and business agility.

A Model for the Future of ERP Partnerships

The Wipro–Infomind.ai collaboration represents a new generation of strategic partnerships where system integrators and technology innovators combine their strengths to deliver greater value. It showcases how AI-powered testing and training automation can transform ERP programs from the ground up.

As the partnership expands, both organizations remain focused on helping enterprises achieve operational excellence through speed, intelligence, and continuous improvement.

Partner With Us

Infomind.ai has already partnered with multiple global system integrators and is in the final stages of collaboration with several others. Our go-to-market model is exclusively partner-driven. We work with system integrators to deliver measurable value, faster project delivery, and higher client satisfaction to their ERP customers.

If your organization is exploring ways to enhance ERP delivery, reduce manual effort, and empower clients through AI-driven automation, we invite you to connect with us.

Together, we can accelerate ERP transformation and redefine what intelligent automation can achieve.

The Future of Infor ERP Training | From Manual SOPs to AI-Generated Videos

Jerome Josephraj — Fri, 10 Oct 2025 10:05:42 GMT

Infor ERP implementations have traditionally followed a train-the-trainer approach. The system implementer conducts face-to-face sessions for a few key users at the client site, who are then expected to train others. While this may seem practical, it’s actually cumbersome, inefficient, and resource-intensive.

The real problem lies in who these trainers usually are. They’re often the organization’s most capable and experienced functional experts — people who deeply understand the business and directly influence growth. When these critical resources spend their time training others, the business pays a hidden cost: their focus shifts away from strategic, value-adding work. As a result, overall business momentum slows, and training itself suffers because these experts are not dedicated trainers.

The challenge becomes even greater when trained users leave the organization. Critical know-how disappears, business continuity is disrupted, and the entire cycle of training and retraining begins again.

Many organizations try to solve this with training documents — long manuals and SOPs that take weeks to create, quickly go out of date, and are rarely referred to by end users. They are difficult to navigate, and when users are under pressure, finding relevant information in these documents is almost impossible. Video training faces similar challenges — time-consuming to produce and even harder to keep current.

And when training must be delivered in multiple languages for global rollouts, the cost and complexity escalate to a point that’s almost unmanageable.

These pain points inspired us to create a smarter solution. Our goal was clear:

Training should not be resource-intensive.
It should be easy to use and navigate.
Users should find answers instantly.
Training must evolve with the system.
And it should be customized for each client, not generic.

We already had the foundation — Intelligent Process Tester (IPT), our no-code testing platform for Infor ERP. By extending IPT with AI large language models and custom algorithms, we transformed it into a training engine that automatically generates AI-powered training videos from existing test scripts — in just a few clicks and in over 100 languages.

Here’s how each pain point is solved:

Not resource-intensive: Videos are generated from test scripts automatically, cutting effort by over 95%.
Easy to use: A built-in ChatGPT-style search lets users ask questions in plain language and jump straight to the exact training video or step they need.
Always up-to-date: When systems change, updated test scripts regenerate new videos instantly — ensuring training never lags behind the software.
Client-specific: Since videos are built from real client test scripts and data, they’re automatically customized to each organization’s processes.

The result is a seamless, scalable, multilingual training experience that evolves with your ERP system — and customers are already reporting ROI exceeding 250% from day one.

The future of Infor ERP training isn’t about static SOPs or manual workshops. It’s about living training content that keeps pace with your business — powered by AI.

AI-Powered Scenarios: Smarter, Faster ERP Testing

Jerome Josephraj — Wed, 01 Oct 2025 15:52:32 GMT

Smarter Scenario Generation: How IPT is Transforming ERP Testing

One of the biggest challenges in ERP testing is scenario design. Business teams know their processes, but translating those into structured test scenarios with input data, validations, and edge cases takes time and expertise. With large Infor rollouts, the number of scenarios quickly grows into the hundreds, if not thousands.

With our new Scenario Generation functionality in Infomind's Infor CloudSuite ERP Testing Automation Tool (Intelligent Process Tester - IPT), we’ve made this process faster, smarter, and more business-friendly.

From BPMN to Scenarios in Minutes

Many organizations already use BPMN diagrams to map business processes. IPT now allows users to upload a BPMN, from which our engine automatically generates all possible flows. Users can review these flows and instantly:

Create their own scenario manually, or
Use AI-assisted generation to let the system build scenarios automatically.

AI-Generated Positive and Negative Scenarios

Users can specify how many positive and negative scenarios they want the AI to create. The system doesn’t stop at generating steps—it also proposes:

Input data (what values should be entered)
Expected outcomes (what the scenario should validate with asserts)

This ensures every scenario has a clear validation purpose, saving hours of manual design work.

Continuous Learning with RLHF

The real innovation is how IPT learns from user interaction. If a tester modifies input data or adjusts validations, IPT uses reinforcement learning with human feedback (RLHF) to learn these preferences. Over time, the system adapts to:

The organization’s unique data sets
Specific validation rules relevant to the project
The preferred style of scenario design

This means the more IPT is used, the smarter it becomes—tailoring scenarios more closely to the business.

Why This Matters for Infor Rollouts

For management, this isn’t just a technical improvement. It has a direct impact on rollout success:

Faster ramp-up: Hundreds of scenarios can be generated in days, not weeks.
Higher coverage: AI ensures edge cases and negative paths are not missed.
Lower cost: Less manual effort from consultants and testers.
Better fit: Scenarios evolve with your project and business rules.

A New Era of Test Design

With Scenario Generation, IPT moves beyond being a test automation tool—it becomes a business process validation assistant. It empowers organizations to go live with confidence, knowing that both common and exceptional process paths are thoroughly tested.

Infor Rollouts: From Rollout to Continuous Improvement

Jerome Josephraj — Tue, 23 Sep 2025 10:06:51 GMT

Infor Rollouts: From Rollout to Continuous Improvement

Rolling out an ERP like Infor LN or M3 is a major milestone for any organization. It involves months of planning, process mapping, testing, and training. But here’s the challenge: too often, businesses treat the go-live as the finish line, when in reality, it’s just the starting point.

With complex ERP systems, change is constant; whether it’s new business requirements, compliance updates, or system upgrades. The organizations that truly succeed are those that treat their Infor rollout as the foundation for continuous improvement.

The Pitfalls of a “One-and-Done” Rollout

Many rollouts focus all resources on getting live, with little thought for what comes next. This creates risks:

Processes drift from the design as teams adapt manually.
Testing becomes reactive, only happening when issues surface.
Upgrades are delayed or resisted due to fear of breaking critical functionality.

The result? The ERP system no longer reflects the actual business and becomes harder to change over time.

Moving to Continuous Validation

This is where Intelligent Process Tester (IPT) makes a difference. With IPT, testing and validation aren’t one-time rollout tasks; they become part of business-as-usual:

Automated regression tests ensure every process continues to run correctly after changes.
Scheduled runs validate processes weekly, giving early visibility of risks.
Tagged scenarios allow focused testing on high-impact areas when changes are introduced.

Instead of fearing change, organizations can embrace it—confident that IPT will catch issues before they reach production.

From Testing to Training

Continuous improvement isn’t just about systems; it’s also about people. That’s why pairing IPT with Intelligent Training Academy (ITA) is so powerful. Every validated scenario can generate training videos and course material automatically. This ensures:

New users are onboarded quickly.
Existing users are retrained as processes evolve.
Business adoption keeps pace with system changes.

The Management View

For Infor program sponsors and executives, continuous improvement translates directly to value:

Reduced risk with every change.
Lower cost of ownership as testing is automated and training content is auto-generated.
Greater agility to adapt to new markets, compliance needs, or customer demands.

The New ERP Mindset

Go-live is no longer the end of the ERP journey. It’s the beginning of a cycle of validation, learning, and improvement. With IPT and ITA, organizations can shift from rollout mode to a continuous improvement mindset, ensuring that Infor remains a living system that grows with the business.

Infor Automation Testing – Best Practices

Jerome Josephraj — Mon, 22 Sep 2025 06:01:28 GMT

This guide outlines recommended practices for building and maintaining high-quality tests in the Intelligent Process Tester (IPT) platform to test Infor ERP. These practices are designed to ensure that tests are reliable, maintainable, reusable, and easy to understand, even for users with limited test knowledge.

1. Keep Scenarios Independent

Each test scenario should be able to run on its own, without relying on the outcome of another test.

Benefits: Reduces flakiness, supports parallel execution, and makes debugging easier.
Example: Do not assume that a customer created in Scenario A will be available in Scenario B. Each scenario should handle its own data needs.

2. Use Hooks for Reusable Processes Only

Hooks should be reserved for processes that are always needed across multiple scenarios.

Common examples: Login, user session setup, or global data initialization.
Avoid overusing hooks, as they make the test flow less explicit for new readers.

3. Use Modules for Reusable Steps

If steps (not whole processes) are repeated across scenarios, place them in modules rather than hooks.

Example: “Create Sales Order” or “Approve Invoice” can be a module.
This improves readability and ensures that scenarios remain transparent and easy to maintain.

4. Prioritise Element ID Over XPath

When identifying UI elements, use stable locators such as IDs or data-attributes.

IDs are more reliable and faster to locate.
XPath should be avoided unless no other selector is available, as it is brittle and breaks easily when the UI changes.

5. Do Not Hard-Code Environment-Specific Details

Avoid embedding environment-specific values (like URLs, usernames, or database connections) directly in scenarios.

Use environment configuration files instead.
Example: Instead of hard-coding test-user@company.com, reference it from a config file.

6. Always Use Secrets for Passwords

Passwords and sensitive information must never be stored in plain text.

Store them securely in your secret manager or IPT’s secure storage.
This prevents accidental leaks in shared repositories.

7. Prioritise API Over UI Wherever Possible

Use APIs for data setup, validation, or process testing instead of UI steps.

APIs are faster, more stable, and reduce test execution time.
Reserve UI automation for validating the user experience, layout, and end-to-end flows.

8. Use UI Only for UX Validation, Not for Variations

UI tests should focus on verifying the user journey and visual behavior, not on testing multiple variations of the same logic.

Example: If a purchase order approval process works via API, test only one user flow in the UI. Avoid repeating multiple variations of approval conditions through UI, since that is better covered via API.

9. Ensure Clear Naming Conventions

Use consistent and descriptive names for scenarios, modules, and steps.

Example: Instead of “Scenario1”, use “Customer_Creation_Valid_Data”.
This helps business users and non-technical stakeholders understand the purpose of each test.
Use this link as a sample naming standard and either use this or come up with your own naming standard that should be followed throughout the project https://docs.google.com/document/d/1O3vG38Q59h8UdOmwPfXJuyweWscdlmfrLGzx-p7WiTQ/edit?usp=sharing

10. Maintain Test Data Strategy

Use synthetic or anonymized test data wherever possible.

Avoid dependencies on production data.
Clean up test data after execution to prevent clutter and conflicts.

11. Keep Scenarios Short and Focused

A test should validate a single business process or user journey.

Long and complex scenarios are harder to debug.
Break down larger flows into smaller, modular scenarios.

12. Review and Update Regularly

Tests must evolve with business processes.

Conduct periodic reviews to remove obsolete scenarios.
Keep modules updated so that changes flow consistently across all dependent scenarios.

Infor ERP Testing to User Training Using AI

Jerome Josephraj — Thu, 11 Sep 2025 19:39:14 GMT

ERP Testing to Training Using AI: How GPT‑Powered Automation Is Re‑wiring ERP Enablement
(From QA to Continuous Learning)

The 40 % Problem

Industry research shows that training alone absorbs around 15 % of an ERP project’s budget, while software testing can account for 20 – 40 % of total development spend; combined, these two activities routinely consume close to 40 % of overall project costs.[1][2] Generative AI is turning that cost curve on its head. Large‑language models (LLMs) such as GPT‑4o now draft, optimize, and even run test cases in minutes. Better still, the very assets created for quality assurance can be recycled into narrated, multi‑language training videos and injected straight into an LMS. Every test you write becomes the next lesson your users watch.

Closing the Loop: Test Case → Script → Video

Legacy pain point	GPT‑enabled fix	Tangible benefit
Consultants manually document business steps in spreadsheets.	Business steps are captured once; the platform converts them to executable test scripts	Up to 70 % faster script authoring.[3]
Scripts “rot” after every sprint.	Prompt‑based refactoring rewrites only what changed.	≈ 50 % lower maintenance effort.[4]
QA → L&D hand‑off is manual.	One‑click video synthesis turns screenshots into branded MP4s.	Training lands the same day UAT is signed‑off.
Static training libraries.	Auto‑re‑rendering updates only changed frames & narration in 100+ languages.	Always‑current content, globally.

Vision‑enhanced models capable of visually inspecting the UI and logging defects are on our near‑term roadmap.

Introducing Infomind.ai for Infor ERP

Infomind.ai, in partnership with Wipro’s Infor alliance, has pioneered an AI-first platform that transforms test assets into dynamic training content, redefining how enterprises enable their ERP users:

Module	What it does
No-Code Test Author	Uses captured business steps (or BPMN diagrams for reference) to generate executable scripts.
Auto‑Execute Engine	Runs scripts across CloudSuite environments, collecting screenshots and KPIs.
AI Video Studio	Creates multi‑language MP4/HTML5 clips from test runs with synthetic voiceover.
LMS Connector	Publishes videos, PDFs, and quizzes to the customer’s learning portal in 100+ languages.

*Tech stack.* Prompts route to GPT‑4o or Claude Sonnet 3.5 (private Azure endpoints optional). Custom RLHF pipelines preserve ERP terminology and enforce security & privacy.

*No code required.* Business users explain each process via BPMN diagrams; the engine generates, validates, and schedules tests—no Java, no Selenium IDE—while keeping business language intact.

Case Spotlight – New Wave Group (NWG)

NWG, a rapidly growing fashion & lifestyle conglomerate, needed to “do more with less.” Too many processes were still manual. The company dismantled an aging facility and stood up a fully automated warehouse while implementing Infor CloudSuite Fashion and Infor WMS — all in just seven months.

Full warehouse automation and CloudSuite Fashion live in 7 months—including all system integrations.
AI‑driven testing slashed manual QA effort and enabled go‑live on schedule despite a parallel facility rebuild.
Multi‑language training videos is accelerating multi-country roll‑outs.

“We implemented full warehouse automation and Infor CloudSuite—with all integrations—in just seven months. The AI‑based project tools from Infomind made it all possible.”
- Patrik Broman, CEO, New Wave Group

→Watch 45-Second Video Testimonial from CEO

Hearing directly from Patrik Broman drives home the real‑world impact of AI‑driven test automation and multi‑language training on rollout speed and user adoption.

Why It Matters

Reclaims up to 20 % of total project budget by shrinking testing & training spend.
Eliminates “code‑freeze” anxiety through continuous, automated QA coverage.
Ships micro‑learning with every release, reducing user ramp‑up time by >60 %.
Creates a searchable knowledge base (video + transcript) for on‑demand support.

What’s Next

Vision‑based assert detection (goodbye XPath).
Embedded copilots offering real‑time test suggestions and in‑app tooltips.
Self‑healing processes where a failed test triggers GPT to propose fixes, regenerate scripts, and update videos before the daily stand‑up.

Call to Action

Curious how Infomind.ai for Infor ERP can compress timelines and slash costs?

Why Infomind.ai (Contains Demo videos)
Email: jerome@infomind.ai

References

[1] IDC Learning Services, “Building a Budget for ERP Training,” 2020.
[2] Idealink Tech, “Understanding Software Testing Costs,” 2025.
[3] KPMG Low‑Code QA report, 2024.
[4] itConvergence AI Testing study, 2025.

Why Infomind.ai Exists (and Why It Matters)

Jerome Josephraj — Thu, 11 Sep 2025 13:39:53 GMT

Our mission is simple: make it faster, easier, and far less expensive for businesses to roll out and manage ERP systems (Enterprise Resource Planning), especially complex platforms like Infor CloudSuite.

Like most innovations, Infomind.ai was born from necessity. We saw how teams struggled with existing tools while trying to automate Infor CloudSuite projects, and we knew there had to be a better way. Instead of forcing one-size-fits-all tools into a highly specialized system, we built an end-to-end solution designed specifically for Infor.

Our ultimate vision: a smoother, faster, less risky ERP journey—covering implementation, user adoption, and ongoing support.

In essence, following featured image shows our high level vision to achieve this mission

Our Journey So Far:

We began by solving two of the most painful challenges in ERP rollouts: Testing and User Training.

Infor Testing Platform: Building Reliable Rollouts

Our first product is a purpose-built testing platform for Infor CloudSuite.

Instead of relying on generic tools, this platform was designed from the ground up to handle Infor’s unique complexities. It lets teams:
- Map workflows visually instead of writing code.
- Easily automate these workflows into test cases using our no-code platform, which can then run across different data sets.
- Handle secure logins and two-factor authentication seamlessly.
- Generate AI-powered reports that are easy for testers and executives to understand.
By streamlining testing, this platform not only reduces rollout costs but also helps avoid costly mistakes before they happen.
AI-Driven Onboarding: Rapid Adoption, Reduced Costs

Rolling out a multi-million-dollar ERP project means little if employees don’t use it effectively. Adoption is often the deal-maker or the deal-breaker.

Our training and onboarding platform changes the game by reusing the same automation scripts created for testing. With AI, it instantly turns them into:
- Step-by-step video guides in over 150 languages.
- Interactive courses that employees can access from a central hub.
- A ChatGPT-style interface where users can ask questions and receive instant, video-based guidance.
This ensures employees don’t just “get trained once and forget.” They have ongoing, on-demand support to keep learning at their own pace—all while reducing traditional training costs.

The Road Ahead: AI-Enabled Support
We're not stopping there. Our vision for the "Future of ERP through AI" extends to ongoing support. We are actively developing our third product: an AI-enabled support solution. This will empower support personnel to quickly get answers to any queries related to Infor and specific customer implementations, providing instant, accurate guidance. This will further reduce the ongoing support costs and enhance the efficiency of your support teams.

At Infomind.ai, we are genuinely excited about making Infor CloudSuite rollouts smoother, faster, and less risky, from initial testing to seamless user adoption and efficient ongoing support. We believe that by leveraging AI across the entire ERP lifecycle, we can truly transform how businesses interact with their critical systems.

If you'd like to explore this journey with us, whether as a client, partner, or just someone curious, drop us a note at jerome@infomind.ai. We'd love to chat.

blog

How to Implement Infor ERP in Half the Time?

Here’s what happens when AI is embedded across every phase of an ERP implementation:

So what actually changes when AI is embedded across the ERP implementation lifecycle?

Want to Go Deeper?

Will AI Replace ERP Consultants?

AI is about to make that excuse disappear.

Phase 1: Requirements — From Months of Analysis to Minutes

WHAT THIS MEANS FOR YOUR ROLE

Phase 2: Configuration — Natural Language Meets Complex Systems

WHAT THIS MEANS FOR YOUR ROLE

Phase 3: Testing — The End of Script-Writing Drudgery

WHAT THIS MEANS FOR YOUR ROLE

Phase 4: Training — A Paradigm Shift, Not an Upgrade

WHAT THIS MEANS FOR YOUR ROLE

Phase 5: Support — Institutional Memory, Finally Preserved

WHAT THIS MEANS FOR YOUR ROLE

So, Will AI Replace ERP Consultants?

Want to Go Deeper?

ERP Test Automation Best Practice: Scenario Independence

Why Scenario Independence Is the Cornerstone of Scalable Test Automation

1. The Real-World ERP Automation Problem

2. The Right Way — Scenario Independence

3. Reusability Without Dependencies — The Infomind Hooks

4. The Big Question — Testing Long ERP Processes

5. Summary Visual — The Evolution of Maturity

Final Takeaway

Why Wipro Partnered with Infomind.ai?

Driving ERP Efficiency Through Intelligent Process Automation

Why Wipro Chose Infomind.ai

Delivering Tangible Results for Enterprise Clients

A Model for the Future of ERP Partnerships

Partner With Us

The Future of Infor ERP Training | From Manual SOPs to AI-Generated Videos

AI-Powered Scenarios: Smarter, Faster ERP Testing

Smarter Scenario Generation: How IPT is Transforming ERP Testing

From BPMN to Scenarios in Minutes

AI-Generated Positive and Negative Scenarios

Continuous Learning with RLHF

Why This Matters for Infor Rollouts

A New Era of Test Design

Infor Rollouts: From Rollout to Continuous Improvement

Infor Rollouts: From Rollout to Continuous Improvement

The Pitfalls of a “One-and-Done” Rollout

Moving to Continuous Validation

From Testing to Training

The Management View

The New ERP Mindset

Infor Automation Testing – Best Practices

1. Keep Scenarios Independent

2. Use Hooks for Reusable Processes Only

3. Use Modules for Reusable Steps

4. Prioritise Element ID Over XPath

5. Do Not Hard-Code Environment-Specific Details

6. Always Use Secrets for Passwords

7. Prioritise API Over UI Wherever Possible

8. Use UI Only for UX Validation, Not for Variations

9. Ensure Clear Naming Conventions

10. Maintain Test Data Strategy

11. Keep Scenarios Short and Focused

12. Review and Update Regularly

Infor ERP Testing to User Training Using AI

ERP Testing to Training Using AI: How GPT‑Powered Automation Is Re‑wiring ERP Enablement(From QA to Continuous Learning)

The 40 % Problem

Closing the Loop: Test Case → Script → Video

Introducing Infomind.ai for Infor ERP

Case Spotlight – New Wave Group (NWG)

Why It Matters

What’s Next

Call to Action

References

Why Infomind.ai Exists (and Why It Matters)

Our Journey So Far:

We began by solving two of the most painful challenges in ERP rollouts: Testing and User Training.

Phase 3: Testing — The End of
Script-Writing Drudgery

ERP Testing to Training Using AI: How GPT‑Powered Automation Is Re‑wiring ERP Enablement
(From QA to Continuous Learning)

The 40 % Problem

Closing the Loop: Test Case → Script → Video

Case Spotlight – New Wave Group (NWG)