Cerebe — the advanced memory + meta‑learning platform for AI products.

Stop context engineering. Power PM & QE copilots that remember your domain and improve every week. Built‑in cognitive chat and multi‑agent deliberation—both grounded in memory.

Cerebe Core

Platform

Memory Graph

Durable cross‑artifact memory (PRDs, Jira, PRs, CI, incidents, UX). Schemas & policies; PII tagging; embeddings + symbolic links; evented changes.

Context Router

Role/task‑aware retrieval with guardrails (size, cost, provenance). Rapid assembly with caching; deterministic prompt provenance.

Meta‑Learning Loop

Evals (gold sets, LLM‑as‑judge), regression guards, dashboards for quality/latency/$; continuous policy improvement.

Technology

Architecture & Flows

Tip: click a box to see details Enter/Space works too.
Cerebe architecture Apps on top (PM Copilot, QE Copilot), Cerebe Core in the middle (Memory Graph, Context Router, Meta‑Learning), Cognitive Chat and Multi‑Agent inside Core. Integrations & Observability support Core from below. PM Copilot Brief → PRD → AC → Test Plan QE Copilot Generate & maintain tests • Flake triage Cerebe Core Platform Core Components Memory Graph PRDs, Jira, PRs, CI, Incidents Schemas • Retention • PII tags Context Router Role/task‑aware • Provenance Rapid assembly • Caching Meta‑Learning Loop Evals • LLM‑as‑judge • Guards Quality • Latency • Cost tracking Cognitive Chat Streaming tool‑use • Memory‑grounded Multi‑Agent Deliberation Debate/reflect/act • Shared scratchpad Integrations & Data Sources GitHub • GitLab • Jira • Slack • Playwright • Postgres • Milvus • vLLM • Kafka • OTel Observability OpenTelemetry • provenance • budgets
Solutions on Core

PM & QE Copilots

PM Copilot — brief → PRD → AC → Test plan

  • Generate & maintain PRDs and acceptance criteria from briefs and history.
  • Live traceability to code & tests through the Memory Graph.
  • Works via cognitive chat or task forms; multi‑agent refinement for complex specs.
Spec defects ↓Cycle time ↓Traceability ≥ 80%

QE Copilot — tests that remember

  • Generate & maintain E2E/API tests grounded in business rules and incidents.
  • Flake triage + auto‑repair; failure → requirement mapping.
  • Multi‑agent proposals for stable selectors & repairs, with full provenance.
Time‑to‑coverage ↑ 30–50%Flake rate ↓ 25–40%Escaped defects ↓ 20–30%
Forward‑Deployed Engineering

8–12 week pilot, KPI‑backed

Milestones & pricing on request; expansion only after KPI hit.

Integrations

Works with your stack

GitHub · GitLab · Jira · Slack · Playwright · Cypress · Postgres · Milvus/pgvector · vLLM/LLM APIs · Kafka/Redpanda · OpenTelemetry

Security

Enterprise‑ready

Get started

Book a Workshop

Tell us about your repos, CI, and current QA/Product pain in a workshop. We’ll respond within one week with a transformation plan.

Contact us to book a Workshop
Docs

Developer quickstart - coming soon!

# Python
cerebe.ingest.document(...)
cerebe.context.route(...)
cerebe.eval.submit(...)
POST /agents/deliberate ...
wss://api.cerebe.ai/ws/chat?session=...