Memory Layer for your Agents

Scoped memory for your agents

Odyssey is a governed memory layer for AI systems. Ingest knowledge, retrieve grounded context, enforce usage, and inspect the evidence behind every retrieval across projects, agents, and customers.

Project-scoped memory
Evidence-first retrieval
Usage enforcement
Scope
Per project
Memory, keys, and usage stay isolated.
Retrieval
Hybrid
Lexical, semantic, recency, and graph signals.
Visibility
Auditable
Requests, evidence, and limits stay inspectable.
Odyssey retrieval
Governed context, scoped by project
Live request
Request ID
req_7fd2a1
Scope
project: active
Status
200 ok
Latency
148 ms
Query
What changed in the vendor renewal policy?
Evidence

Retrieved chunks, source documents, and references stay visible and inspectable.

Scope

Requests are tied to a project and API key, with access boundaries enforced server-side.

Logs

Retrievals, latency, and downstream model calls can be inspected after the fact.

Limits

Usage caps protect you when a tenant or agent starts going sideways.

Response shape/api/v1/retrieve
{
  "items": [...],
  "count": 5,
  "meta": {
    "project_id": "proj_...",
    "graph_used": true,
    "api_key_id": "key_..."
  }
}
The problem

Most AI memory stacks break exactly where production starts

A vector database can store embeddings. It does not automatically give you tenant isolation, evidence visibility, request auditability, or usage enforcement. That gap is where agent systems get expensive, unstable, and hard to trust.

Ungoverned memory

Without hard project boundaries, your retrieval layer becomes one shared soup of documents, embeddings, and accidental cross-tenant risk.

Untraceable answers

When an answer is wrong, most teams cannot quickly see which chunks influenced it, which query path was used, or how the system got there.

Operational blind spots

Agents can retrieve forever, spend unpredictably, and hammer infrastructure unless limits and counters are enforced where requests actually execute.

Why Odyssey

Odyssey governs memory for AI systems

It sits between your application and your retrieval layer. You keep your product UX. Odyssey governs how knowledge is ingested, scoped, retrieved, measured, and audited.

Project-scoped memory

Documents, chunks, API keys, logs, and usage all stay bounded to a project so each customer or environment behaves like its own memory domain.

Evidence-first retrieval

Every retrieval returns traceable memory items and can be inspected later. You can see what influenced the result instead of guessing.

Usage enforcement

Ingest and retrieve calls are checked against limits per project and API key so cost and abuse controls live in the execution path, not in wishful middleware.

Control plane

More than retrieval. A control plane around memory.

Odyssey is designed to be your memory infrastructure: state is scoped, access is enforced, requests are measured, and outputs stay tied to evidence. That is what makes memory survivable in production.

Scoped projects

Treat each customer, workspace, or environment as its own governed memory domain.

API key boundaries

Requests run under explicit key scope and project scope, not vague client-side assumptions.

Operational telemetry

Track retrievals, model calls, latency, and usage as first-class signals.

Traceable retrieval

See what was retrieved, why it ranked, and what influenced the result.

How it works

Three steps from raw knowledge to governed retrieval

1
Ingest knowledge

Upload source material like SOPs, specs, tickets, contracts, and internal docs. Odyssey chunks, embeds, and stores them inside a project boundary.

2
Retrieve grounded context

Your app or agent calls Odyssey instead of raw vector search. Retrieval blends lexical, semantic, recency, and graph-aware signals.

3
Inspect and enforce

Review evidence, request logs, API key activity, and usage counters so you can debug behavior and clamp cost before customers do it for you.

Product surface

Built for the teams wiring memory into real systems

Odyssey gives you the operational surface around memory, not just a place to throw vectors.

API surface

Minimal API surface. Infrastructure-level behavior.

The interface stays simple. The behavior underneath does the heavy lifting: project scoping, usage checks, evidence logging, and retrieval control.

Ingest
POST /api/v1/ingest
Retrieve
POST /api/v1/retrieve
Example request
api key
curl -X POST "https://your-domain.com/api/v1/retrieve" \
  -H "x-api-key: $ODYSSEY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "What changed in the vendor renewal policy?",
    "limit": 10
  }'
Isolation
Per project
Memory, keys, and usage stay scoped.
Retrieval
Hybrid
Lexical, semantic, recency, and graph signals.
Controls
Usage caps
Protect projects from runaway agents.
Auditability
Evidence visible
Inspect what influenced the result.
Use cases

Where Odyssey fits

AI copilots

Ground responses on project-scoped knowledge while preserving evidence and usage visibility across customer workspaces.

Agent systems

Replace fragile custom memory glue with a governed retrieval layer that can be measured, replayed, and constrained.

Infra & ops teams

Use logs, limits, and request-level visibility to catch regressions, debug bad answers, and enforce cost boundaries.

Get started

Start building on governed memory

If your AI product needs memory that can survive real customers, real traffic, and real cost, Odyssey gives you the missing layer: scoped memory, evidence-first retrieval, and hard operational controls.