Case study · B2B revenue control · verified replay
Your CRM says commit. Does the buyer?
Deal Rescue and Forecast Truth compares seller-entered confidence with exact buyer language, stakeholder coverage, dated commitments, and sales activity. It rebuilds the forecast, drafts the next useful move, and stops before any buyer or CRM action.
Deal Rescue and Forecast Truth demonstrates a governed route from fragmented deal evidence to an explainable forecast and manager-reviewed rescue plan without allowing a language model to invent probability, rewrite source evidence, or execute an external action.
Live interface
Inspect the replay before the architecture.
The screen below is the current public system using synthetic scenario data. It does not expose client production records or perform an external write.
Deal Rescue and Forecast Truth
Synthetic buyer evidence challenges seller confidence, rebuilds the forecast, and stops at a manager decision gate.
Inspect the live surface →
Case-study figures describe this documented engagement and are not forecasts or guarantees.
The operating constraint
CRM forecasts often preserve seller confidence after buyer evidence has changed. Budget may remain unapproved, the economic buyer may be absent, security or legal review may still be open, the next step may belong only to the seller, or the buyer may have stopped responding. Managers need the exact evidence and a controlled recovery path, not another generated summary.
The system Aixcel designed
Aixcel built a typed FastAPI control plane with six parallel LangGraph evidence roles for data contract, conversation evidence, objection intelligence, stakeholder coverage, engagement risk, and commitment integrity. Bounded forecast, rescue, policy, and manager stages join that evidence. Deterministic Python owns source hashes, privacy screening, risk and exposure bounds, forecast policy, tenant and role authorization, quotas, idempotency, and the zero-mutation boundary. PostgreSQL, SQLAlchemy, Alembic, durable LangGraph checkpoints, signed serverless receipts, OpenTelemetry, Prometheus, JSON logs, evaluations, Docker, and GitHub Actions complete the operating path.
The documented result
The public decision room is a live system rather than a fixed animation. A reviewer can change seller confidence, stakeholder counts, buyer silence, next-step integrity, and the latest buyer statement. The verified browser journey changed an evidence-backed Commit at 0 risk into Omitted at 100 risk. The release passed 53 automated tests, 83.97 percent measured coverage, 12 of 12 expected risks, top risks, and forecast categories, 15 evaluation dimensions, 28 live Postman assertions, 16 Prometheus signal families, PostgreSQL checkpoint recovery across an API restart, persistent dark and light themes, and zero external mutations.
System components
Python 3.12, FastAPI, Pydantic v2, LangGraph, SQLAlchemy, PostgreSQL 17, Alembic, REST, OpenAPI, Postman, OpenTelemetry, Prometheus, Docker, GitHub Actions, Playwright, Vercel
How to interpret this evidence.
Names and sensitive details are withheld. Metrics retain their stated meaning and evidence label. A scope count is not converted into an outcome, and no engagement result is presented as a universal benchmark.
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