Interloom

https://interloom.com/

German startup. Captures how real work is performed across enterprise systems and teams; converts process knowledge into a persistent memory layer agents use to automate complex workflows. Targets the tacit-knowledge gap that agents currently lack.

At a glance

Type
Enterprise tacit-knowledge memory
Tier
T1
Created
2026-03
Latest release
not applicable — not OSS
License
not applicable — not OSS
GitHub
not applicable — no GitHub repo
Pricing
Enterprise pricing; no setup fees; fixed-price per interaction (contact sales)
Funding
$16M total Seed · 2026-03

Taxonomy

storage
proprietary
retrieval
extraction-pull
persistence
long-term
update
extraction
unit
skill
governance
auditable
conflict
none

When to use

Optimised for: enterprise tacit-knowledge capture + governance

Anti-fit: not for consumer / individual use

Pros & cons

Pros

Memory-as-context-orchestration positioning — focuses on what to inject when, not just what to store.

Cons

Newer entrant with limited track record; orchestration framing may overlap with what LangGraph and similar tools already address.

Claims & capabilities

$16.5M seed (March 2026, DN Capital). Customers: Zurich Insurance, JLL, Fiege, Commerzbank, Volkswagen. Processing millions of enterprise cases.

Technical surface

API surface
searched not found
Backend storage
searched not found
Deployment
Three modes: managed multi-tenant cloud; dedicated single-tenant; BYOM (bring your own model/endpoints)
Embedding model
searched not found
Multi-tenancy
searched not found
MCP
not documented publicly
A2A
not documented publicly
OpenTelemetry
not documented publicly

Similar systems

Other dedicated memory layers in the catalog, ranked by inbound references.

  • Mem0 T1

    Universal memory layer for AI agents. Three concurrent stores (vector + graph + KV); LLM-extracted facts; concurrent retrieval via ThreadPoolExecutor.

  • Zep & Graphiti T1

    Bi-temporal knowledge graph (event time + ingestion time). Strong on chronological reasoning and contradiction tracking. Graphiti is the open-source core.

  • Cognee T1

    "Extract–Cognify–Load" pipeline that turns raw input into a typed, queryable knowledge graph for agent recall.

  • Hindsight (Vectorize) T1

    Standalone memory service from Vectorize. Open source. Biomimetic four-network design (World, Bank, Observation, Opinion). Ships an MCP memory server.

  • Memvid T2

    Single-file memory layer (one .mv2 file). No DB, no server. Append-only sequence of immutable Smart Frames with timestamps + checksums. Native Rust core (rewritten from Python).

  • Supermemory T1

    Memory engine with API, app, browser extension, and MCP server. Extracts facts, tracks updates, resolves contradictions, auto-forgets expired info. Plugins for Claude Code, OpenCode, OpenClaw, Hermes.

Row last verified 2026-05-14. Catalog data is CC-BY-4.0 — see how to read this.