iKoMatch: an AI fundraising assistant on WhatsApp and voice

The problem

Founders spend months building investor lists in spreadsheets and sending cold emails. iKoMatch wanted a service rather than another tool: a founder chats on WhatsApp, and the system finds the right investors, drafts the outreach and follows up.

What we built

• WhatsApp-first onboarding. The founder sends a pitch deck in chat. The system converts it from any format and reads it, and an AI voice call from our Voice Agents platform fills the gaps. The profile publishes itself; there are no forms.
• A self-growing investor database. A crawler reads financial-press feeds every 6 hours. Four AI gates extract investing organizations and reject startups, banks and brokers, with reasons. Enrichment finds official sites and contacts. Nothing goes live until a reviewer approves it from a side-by-side diff with confidence badges.
• Explainable matching. Rules, then embedding search, then a Gemini re-rank that must give its reasons. Diversity rules stop five near-identical funds from filling a slate, and firms, angels and grants share one 1–10 score.
• Outreach. For 45 days the founder gets a daily slate in chat across six channels: warm introductions, email, LinkedIn, application forms, angels and grants. Emails are drafted, edited in plain language and sent from the founder's own Gmail or Outlook; opens trigger well-timed WhatsApp nudges.
• Operations. A control tower with an approval workspace, a WhatsApp team inbox, a campaign editor and a jobs console where schedules change without a deploy.

How it works in production

The WhatsApp conversation runs on our WhatsApp Agents service, with a role-specific prompt for each registered founder. Background jobs take database advisory locks, so exactly one worker runs each job: no duplicate slates and no double sends. Every external call is logged with service, endpoint, status and duration, with secrets and phone numbers scrubbed. A Razorpay payment activates the founder's plan, thanks them on WhatsApp and refreshes their slate without anyone touching it. More than 100 test files cover routes, services and clients, including an OpenAPI contract test.

Each night the judge grades the previous day's recommendations, and its findings land on a quality dashboard the operations team reviews every day.

What we'd change

• Build the replay harness first. We now test ranking changes by replaying them against the judge's past verdicts, and that replay rejected two plausible-sounding fixes the data didn't support. Before it existed, unit fixtures carried more of the weight than they should have.
• Start as one service. The platform began as separate services and was later merged into one FastAPI backend with one database and one migration history. Starting there would have saved a migration.