Agentic FP&A Platform
Built for AI agents.
Not retrofitted with a chatbot.
EPM Lite is the FP&A platform designed around tool-using AI agents from day one. 35+ agent tools cover ~99% of manual app actions. Every write is drafted, every action audit-trailed. The agentic alternative to Anaplan, Adaptive, and Excel.
What an agentic platform actually means
Most "AI in FP&A" today is a chatbot bolted onto a 2015 planning tool. EPM Lite inverted the design: the agent is the primary interface, traditional grids are the fallback. 35+ tools across four categories.
Read
12 tools
Query fact tables, fetch trial balance, summarize a report, pull audit-log entries, list scenarios.
Plan
10 tools
Update drivers, write member formulas, create scenarios, manage entities and dimensions, schedule connectors.
Forecast
8 tools
Run 15 forecast algorithms, compare with R²/RMSE/MAE/MAPE, lock the winner, run what-if scenarios.
Decide
7 tools
Draft commits, ratify writes, export PDFs, push notifications, manage approvals, query the audit log.
Safety primitives
An agent that can write to your financials needs to be safe by default. EPM Lite's entire write surface is gated behind these four primitives.
Draft-before-commit
Every write produces a card. User clicks Post. Backend re-validates. Then commit happens.
Server-side auth on tools
Tool calls run with the user's permissions. LLM never gets credentials. RBAC enforced at the API layer.
Full audit trail
Every mutation logged: actor, timestamp, before/after JSON. Filterable. Forever.
Streaming + interruptible
Watch the agent run tools live via SSE. Cancel mid-task if it goes wrong.
Common questions
What is an agentic FP&A platform?▾
An agentic FP&A platform uses AI agents — software that can chain multiple tool calls, read and write financial data with permissions, and complete multi-step finance tasks autonomously — rather than just chatbot UIs bolted onto a legacy planning tool. EPM Lite was built around agents from day one: the agent has 35+ tools covering ~99% of manual app actions, every write produces a draft for human review, and every action is audit-trailed.
How is this different from a chatbot in Anaplan or Adaptive?▾
Legacy planning tools added a chatbot bolt-on after the fact — the chatbot can answer questions but the planning model wasn't built for tool-using agents. EPM Lite reversed the design: every primitive (cube schema, RBAC, draft queue, audit trail) is designed for an agent to operate within safely. The agent can plan, forecast, draft writes, run scenarios, and commit changes — not just summarize what's already there.
Is the agent safe? What stops it from messing up my financial data?▾
Three safeguards. (1) Draft-before-commit: every chat-driven write produces a draft card the user must Post. The LLM never auto-mutates the database. (2) Server-side authentication: every tool call runs with the calling user's permissions; the LLM never gets credentials. (3) Audit trail: every mutation logged with actor, timestamp, and before/after JSON. You can prove what happened.
Which LLMs does EPM Lite use?▾
Both Gemini 2.5-flash (default) and Claude Haiku 4.5 are supported, swappable via environment variable. Prompt caching keeps API costs around $0.40/user/month at typical usage. The LLM is configurable per workspace.
What can the agent actually do?▾
Read fact tables, draft entries, run 15 forecast algorithms, commit writes through the draft queue, export reports as CSV/Excel/PDF, manage scenarios and what-ifs, query the audit log, manage drivers and formulas, and answer plain-English questions about the cube. 35+ tools cover ~99% of manual app actions. New tools ship continuously.
Can the agent handle multi-step tasks?▾
Yes. Example: 'Hire 3 engineers and show the runway impact' chains four tool calls — update HEADCOUNT_ENG, recompute SALARIES_ENG via member formula, run runway forecast, render the waterfall card. The user sees each step stream in real time and ratifies the final commit.
Watch the agent run live.
Open the demo, ask the agent a question, watch it chain six tool calls in real time.