Pi Mapper
AI agents need to understand your processes to work reliably - the systems, the workflows, the policies, the exceptions and the approval needs. I help operations teams build the operating model, the process knowledge layer and evals for that.
About
Malika Bhatia
Founder, Pi Mapper
London, UK
I trained as an IT engineer and started my career on the technical side - understanding systems from the inside out. That foundation turned out to be more useful than I expected when I moved into internal consulting, working across group functions and getting close to how large organisations actually operate: the politics, the handoffs, the gap between what IT delivers and what the business needs.
From there I moved into Six Sigma and lean - learning to map how work actually flows, not how it's supposed to. Then outsourcing, where the discipline of handing off processes to third parties forced a rigour about documentation and process clarity that most organisations hadn't needed before. Then large ERP implementations, where the gap between what a system assumes and what an organisation actually does becomes very expensive, very fast.
After that came process automation and RPA - which taught me that automating a broken process just breaks it faster. The underlying process intelligence has to come first. That lesson turns out to apply even more forcefully to AI agents, which are considerably less forgiving than a well-configured RPA bot.
Each wave has raised the bar on how well you need to understand your processes before you embed technology into them. AI is the highest bar yet - and process intelligence, encoded as agent skills, is the foundation that makes it crossable. Get that right, and AI agents become a genuine operational capability. Pi Mapper is my attempt to help organisations build it.
Writing
I write for process owners, operations managers, and the people responsible for making AI investments actually land. No hype, no vendor positioning - just honest thinking on what works and why.
Your documented process is fiction. That's why your AI project is struggling.
Every large operation has two versions of itself. There's the official one - the flowchart in Confluence, the training manual, the SOPs signed off in 2019. And then there's the actual one.
What process mining actually tells you - and what people get wrong about it
Process mining has become a fashionable word in enterprise transformation circles. Most of what gets called process mining is really just process mapping with better software. Here's the distinction that matters.
How to talk to your AI vendor without getting sold a beautiful slide deck
The questions you should be asking before any AI engagement - and the answers that should make you pause.
The rework problem: why AI can predict it but operations teams still don't use it
Rework is one of the most detectable patterns in operational data. It leaves clear traces in event logs. The models can see it coming. So why does it keep happening?
Methodology
Pi Mapper turns the way your processes really run into agent-ready Plugins - across four phases and one tight loop. The output is process intelligence your agents can actually use, with quality and governance built in from the start.
Phase 01
Foundation
Discovery & Process Mining
See the process as it truly runs.
Every good skill starts with how the work really runs. Before writing anything, we map the real process end to end - including the variants, the exceptions, and the rework that never made it into the manual.
Phase 02
Design
Operating Model
Decide how the work runs.
Decide what an agent handles, what plain code handles, and where people stay in charge. Sort out how quality is governed across the whole flow before a single skill is written.
Phase 03
Build ⇄ Test loop
Skill Writing
Translate model into a skill.
Turn the plan into something the agent can actually run. Write clear, versioned instructions, give it the right context and tools, then send it straight to testing.
Phase 04
Build ⇄ Test loop
Evals & Scoring
Prove it against reality.
Find where it breaks, then feed that straight back into the skill. Phases 03 and 04 keep cycling until it clears the bar. Then it's ready to ship.
A Plugin brings it all together - the skill with the connectors, governance, and evals it relies on, shipped as one versioned unit you can trust. That's what makes your process intelligence ready for agents.
From Phase 03
The process logic: instructions, steps, policies, and edge cases.
Systems of record
The system connections and tools the agent works through.
From Phase 02
Guardrails, approvals, audit trail and human-in-the-loop gates.
From Phase 04
The quality bar ships with it, watched live and not just at build time.
From Phases 01–02
Domain knowledge, reference data and the operating model.
Metadata
Version, owner, and dependencies - so it stays easy to trace and update.
In production, the Plugin becomes your next dataset. Live data, new variants, and new exceptions flow back into Phase 01 - and the whole method runs again.
What I do
I take on engagements where I think I can genuinely help - and try to be honest when I'm not the right fit. The work is always practical and grounded in what your teams actually need, not what looks good in a deck.
01
Using event log data to surface how your operations actually run - not how they're documented. The essential foundation before any AI can reason reliably about your processes.
02
Designing the division of labour between your people and AI agents: what agents handle, where humans stay in the loop, and how you avoid the failure modes that come from getting that boundary wrong.
03
Building the empirical grounding layer that AI systems need to reason correctly about your operations - rather than performing confidently against documented fiction.
04
Structured evaluation of AI systems before and after go-live. Are your agents actually doing what you think? Where do they fail, and under what conditions? Honest answers before the stakes get high.
Get in touch
Whether you're in the middle of an AI rollout that's not landing, or you're earlier in the journey and want to think it through - feel free to get in touch. No pitch, no pressure.
malika@pimapper.com"The problem with most AI in operations isn't the AI. It's that nobody bothered to find out what the operations actually look like before they started."
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