AI finance
Hardening an AI finance platform and speeding up its chat so it could win clients.
FigureFlow is an AI-native finance platform for CFOs and finance teams. They needed reliable data, accurate reporting, domain AI agents, and a fast, trustworthy chat experience before finance buyers would commit.
figureflow.appA faster, more reliable finance product with stronger week-four retention.
The challenge
Finance buyers do not tolerate slow or wrong numbers. FigureFlow needed clean data, compliant reporting, and AI agents that could close the books, all running fast enough to feel trustworthy.
The AI chat experience was a sticking point. Some functions and processes were slowing it down, and it was not clear which ones.
The loop they ran
Each move keeps its source, shipped work, and measure attached.
- 01
Capture
Ran a stress test and pulled platform telemetry to see what users actually hit.
- 02
Rank
Ranked the bottlenecks slowing the AI chat by their impact on the experience.
- 03
Spec
Specced the data, reporting, agent, and performance work into clear tasks.
- 04
Ship
Shipped integrations, reporting, AI agents, and the performance fixes.
- 05
Measure
Measured chat latency, accuracy, and key journeys with live monitoring.
What this work shows
FigureFlow
A performance and verification story: isolate the slow paths, ship the fixes, and monitor the journeys that matter.
- Stress-test the AI chat and pinpoint the functions and processes causing slowdown.
- Ship integrations, reporting, domain agents, and targeted performance fixes.
- Verify a 60% faster chat experience with live monitoring and journey benchmarks.
What changed
The result is only as useful as the evidence attached to it.
- week-4 retention measured in PostHog+14%
- AI chat after stress-testing the bottlenecks60% faster
- won as the platform became client-readyNew clients
- reconciliation, journal entry, and reporting automated4+ agents