Generic LLM chat
The black box
Tell it what to do, and hope. The work happens somewhere you can’t see, and you’re left to trust a result you can’t trace or defend to an auditor.
Inside every APM application
Meet KAI.A collaborator, not a replacement.
You cannot close the books by prompting a generic LLM. KAI lives inside Kainam's Augmented Performance Management suite, a fully governed environment where you see every step.
- Consolidation
- Account Reconciliation
- Budgeting & Planning
- Predictive Forecasting
Your counterpart, inside every app.
Same agent. App-native context. The work happens in the product UI, with visibility and audit trails, not in a chat window you hope on.
- Planning
Drivers re-flow with you in the model. KAI proposes; you decide.
- Consolidation
Eliminations and close steps run in view, attributed to named roles.
- Reconciliation
Matches and exceptions surface in the work queue, not a hidden job.
- Forecasting
Scenarios and variance explanations stay inside the living forecast.
Four commitments KAI makes.
What it means for AI to augment people instead of replacing them.
01
Augmentation, not automation of people
KAI makes each person more capable, it doesn't make them redundant. The goal is a stronger operator, not a smaller team.
02
Embedded in-app counterpart
KAI lives inside each application as your counterpart. It knows the app cold and learns your business, not a chatbot bolted to the side.
03
Human-in-command
KAI never runs off on its own. It acts on what you direct, you are always in charge, and judgment stays with named roles.
04
A glass box, not a black box
Generic LLMs go off and do God knows what. KAI shows its work inside a governed environment: visible, attributable, and reviewable before anyone signs off.
Differentiator 02 · Architecture
Three layers. One AI-native fabric.
KAI can operate inside the app and show its work because every function is MCP-exposed. Architecture is what makes the glass box possible.
MCP · agent-operable
Augmented Applications
what you buy
ConsolidationsAccount ReconciliationBudgeting & PlanningPredictive Forecasting
Core Engines
the building blocks
KIMBALL · dataMONZA · analyticsSENNA · predictiveMirador · app builder
Foundation. Multi-cloud, single-tenant
cloud-native, never cloud-locked
Elastic VMsClickHouseMongoDBKeycloakYour cloud or ours
The MCP fabric threads all three layers. Everything is a microservice with an MCP interface, so anything the UI can do, an agent can do, and vice versa. AI-enabled by construction, not by add-on.
Differentiator 03 · AI Philosophy
A glass box, not a black box.
You cannot run EPM by prompting a generic LLM. Finance needs visibility, auditability, and traceability. A chat window has none of that.
Kainam · KAI
The glass box
KAI operates inside a fully governed, fully visible APM environment. You see every step, attributed and reviewable, before anyone signs off.
- Load 5 ledgers · 70,264 recordsKAI
- Currency translation to groupKAI
- Intercompany elimination — runningKAI
- Gate · Controller reviewawaiting
A chat prompt is not a close. KAI: work alongside it, and see.
Tomorrow's competition is not another EPM vendor. It is the idea that you can “just ask an LLM” to close the books. CFOs cannot sign their names on financial accuracy based on a prompt. KAI augments the human inside a governed system, always in your command, and it can do this because of the architecture above: every function is MCP-exposed, so the agent operates the app and proves its work.