Catalog Systems Vertical / domain-specific AI memory Sierra

Sierra

https://sierra.ai

Bret Taylor + Clay Bavor. Agent Data Platform links unstructured conversation data to enterprise systems (billing, inventory, policies, transactions); persists across channels and time. Memory accumulates across every interaction, not just within a session.

Active · Verified 2026-10-23 · fresh as of 2026-10-23 · 60 cited facts, 8 with a third-party source · Suggest a correction

At a glance

Type
Unified customer graph (Agent Data Platform) vendor fix
Tier
T1
Section
Vertical / domain-specific AI memory
Created
2024-02 third-party fix
Latest release
not applicable — not OSS fix
License
not applicable — not OSS fix
GitHub
not applicable — no GitHub repo fix
Pricing
Enterprise only third-party fix
Funding
$1.5B total $15.8B val Series D · 2026-05 third-party fix
Freshness
2026-10-23 fix
Layer
agent-infra repo fix
Licensing
commercial third-party fix
Deployment locus
cloud vendor fix
Platform vs product
platform vendor fix

Memory taxonomy

storage
graph
retrieval
graph-traversal
persistence
long-term
update
extraction
unit
profile
governance
inspectable
conflict
deterministic

When to use

Optimised for: cross-channel customer graph + agent handoff + CRM integration

Anti-fit: not for non-customer-facing use cases

Pros & cons

Pros

Memory model designed around customer-conversation lifecycle (handoff, resolution, recurrence); strong measured deflection in production.

Cons

Closed enterprise product; pricing and integration require enterprise partnership.

Claims & capabilities

$100M ARR in seven quarters. $15.8B valuation after $950M raise (May 2026).

Technical surface

API surface
searched not found
Backend storage
searched not found
Deployment
Managed-only
Embedding model
searched not found
Multi-tenancy
Strict tenant isolation — customer data never shared across tenants; deterministic access to systems of record
MCP
no MCP support advertised — vertical product, no MCP server / client integration documented
A2A
no A2A protocol support advertised — vertical product, no A2A integration documented
OpenTelemetry
no OpenTelemetry integration advertised — vendor logs/observability not publicly documented

Alternatives to Sierra → live options ranked by shared design, licence, hosting and MCP support

Similar systems

Other vertical / domain-specific ai memory in the catalog, ranked by inbound references.

  • Inworld AI T1

    Formerly an NPC character engine with named Long-Term Memory; now sells realtime voice models (TTS-2, STT-1, speech-to-speech) and OpenAI-compatible open-model inference. Character/NPC memory is no longer the headline product.

  • NVIDIA ReMEmbR T3

    Builds long-horizon memory by captioning video segments with VILA, storing captions with timestamps + 3D position coordinates in MilvusDB. At query time, LLM iterates retrieval across text, time, and position modalities. Deployed on Nova Carter robot (Jetson Orin).

  • Abridge T1

    Clinician-assist ambient documentation. Source mapping: every AI-generated summary element traced back to the source utterance. Audit-and-trust layer over episodic memory. Built on proprietary 1.5M+ medical-encounter dataset.

  • ASAPP GenerativeAgent T1

    Treats memory as first-class architecture. Captures the digital footprint of every interaction; retrieves preference and history at engagement time. Public example: airline knowing a frequent flyer wants aisle seats with her son — preference-aware, not just history-lookup.

  • BenevolentAI T1

    Taken private: merged into Osaka Holdings (renamed BenevolentAI S.A.) and delisted from Euronext Amsterdam 2025-03-13. Target identification / drug repurposing / mechanism tracing. 85+ data sources, petabyte-scale, rebuilt every few weeks. Wet-lab results re-enter the graph and shift downstream predictions — institutional experimental memory closing a feedback loop. As of Oct 2026 benevolent.com leads with Qor, powered by BenevolentAI, a life-science intelligence service for biopharma decision makers and consultancies. Qor (qor.one) is a continuously updated decision-intelligence service built on BenevolentAI's knowledge graph and reasoning methods: it tracks evidence on an asset or indication (competitive position, rival readouts, comparable deals), source-verifies each claim and flags when an earlier conclusion stops holding. It targets biotech teams and life-science consultancies.

  • Causaly T1

    Agentic AI platform for life sciences: orchestrated scientific agents over a curated biomedical knowledge graph (plus Bio Graph and Pipeline Graph), an evidence-retrieval system and an enterprise data fabric over literature, trials and patents.

Sources (59 cited facts, 8 third-party)

Each fact links to the page it came from; the badge says who published it (how to read sources).