Cerebe Cognitive Services

Cognitive services
through one API.

The cognitive infrastructure that production agentic AI demands — persistent memory, capability-based LLM routing, versioned prompts, multi-agent coordination, and meta-learning. Stop building plumbing; ship product.

Get an API key → Explore Services
cerebe-sdk — python
>>> from cerebe import Cerebe >>> cb = Cerebe(api_key=...) >>> cb.memory.add("patient prefers morning workouts", ... session="sess_123", type="semantic") { "id": "mem_a4b...", "stored_at": "2026-05-04T16:10:42Z" } >>> cb.llm.complete(prompt="What does Maria prefer?", ... session="sess_123", route="capability:reasoning-fast") { "model": "claude-haiku-4.5", # router picked "answer": "Maria prefers morning workouts.", "memory_hits": 1, "trace_id": "otel_a89..." } >>> cb.evaluate(suite="coaching-tone") ✓ 42/42 evals passed · grafana dashboard →

Two SDKs

One API. Two languages. Cloud or on-prem.

Python and TypeScript SDKs auto-generated from the OpenAPI spec. Contract-tested. Stable across language boundaries. Memory, LLM routing, prompt management, evaluation — all behind the same surface.

Privacy-first deployment: cloud-managed, VPC-deployed, or fully on-prem. Doppler-managed secrets, External Secrets Operator, data residency controls. Your data stays where your contracts require.

SDK docs →

The six services

The cognitive infrastructure
that production agentic AI demands.

Cerebe decomposes into six service surfaces, exposed through one API. Full reference docs live at docs.cerebe.ai.

01

Memory Fabric

Working, episodic, long-term. Qdrant (vector) + Neo4j (graph). Cross-session, multi-tenant, with COPPA-grade entity controls.
02

PLRE Meta-Learning

Plan → Learn → Reflect → Evolve. Domain-agnostic adaptive learning loops. Agents that improve every week without manual tuning.
03

LLM Router

Route by capability, not model name. Switch providers without touching app code. Per-tenant overrides, vendor-portfolio resilient.
04

Prompt Versioning

YAML-managed prompts with semver. A/B evaluation. LangSmith integration. Auto-rollback on quality regression.
05

Multi-Agent Coordination

Shared scratchpad in memory fabric. Deliberation primitives. Multi-agent reasoning grounded in shared context.
06

Python + TypeScript SDKs

Auto-generated from OpenAPI. Contract-tested. Stable across languages. Cloud, VPC, or fully on-prem.

Why Cerebe

What stateless LLM calls leave on the table.

vs. Stateless LLM APIs

Persistent memory across sessions

Plain LLM APIs forget every turn. Cerebe's hybrid memory fabric (vector + graph + temporal) gives agents continuity — they remember the user, the domain, what's been discussed, what worked.

vs. Vendor-Locked Stacks

Model-agnostic by design

OpenAI shops. Anthropic shops. Mistral shops. Open-weights shops. Cerebe routes by capability, not model name. Switch providers without touching app code; switch mid-conversation if a vendor degrades.

vs. DIY Memory + Routing

Months of infrastructure, zero days

Memory fabric, capability router, prompt versioning, eval harness, multi-agent coordination — each is a quarter of engineering work. Cerebe ships all of them behind one API.

vs. Cloud-Only AI Services

VPC + on-prem from day 1

Regulated industries can't ship customer data to a third-party SaaS. Cerebe deploys to your VPC or fully on-prem with the same SDK. Data residency by config.

Get Started

The cognitive backend for production agentic AI.

Persistent memory. Capability routing. Meta-learning. One API. Get an API key and ship your first cognitive call in minutes.

Get an API key →