AI Singapore SEA-LION
SEA-LION-Embedding (March 2026): retrieval + reranking models contrastively trained on 245M text pairs across 10 SE Asian languages. SEA-BED benchmark (169 datasets). SEA-LION v4 (Gemma-based) at 128K context with native function calling.
Active · Verified 2026-10-22 · fresh as of 2026-10-22 · 43 cited facts, 2 with a third-party source · Suggest a correction
At a glance
- Type
- SE-Asian cross-lingual semantic-retrieval memory vendor fix
- Tier
- T2
- Section
- Dedicated memory layers
- Created
- 2023 (first SEA-LION launch) third-party fix
- Latest release
- not applicable — not OSS fix
- License
- not applicable — not OSS fix
- GitHub
- not applicable — no GitHub repo fix
- Freshness
- 2026-10-22 fix
- Layer
- agent-infra repo fix
- Licensing
- commercial vendor fix
Memory taxonomy
- storage
- vector
- retrieval
- similarity
- persistence
- parametric-permanent
- update
- read-only
- unit
- chunk
- governance
- opaque
- conflict
- n/a
When to use
Optimised for: SE-Asian language coverage (10 languages, contrastively trained)
Anti-fit: not for English-monolingual use cases (English-first models perform better)
Pros & cons
Pros
First Southeast-Asian-language-tuned memory model; strong with Bahasa, Thai, Vietnamese.
Cons
Regional scope limits global relevance; smaller English benchmarks coverage.
Claims & capabilities
SOTA on SEA-BED for Burmese, Filipino, Indonesian, Khmer, Malay, Lao, Tamil, Tetum, Thai, Vietnamese.
Technical surface
- API surface
- searched not found
- Backend storage
- searched not found
- Deployment
- Both (free download self-hosted + Amazon SageMaker JumpStart for managed deployment)
- Embedding model
- searched not found
- Multi-tenancy
- searched not found
- MCP
- not supported
- A2A
- not supported
- OpenTelemetry
- not documented publicly
Alternatives to AI Singapore SEA-LION → live options ranked by shared design, licence, hosting and MCP support
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.
- Letta / MemGPT T1
Originated as MemGPT (UC Berkeley), where the model pages its own memory between context, recall and archival tiers. The product now centres on Letta Code, a stateful agent harness whose agents rewrite their own memory, skills and prompts over time.
- Memori T2
Structured, persistent memory layer for AI agents. Open source.
Sources (42 cited facts, 2 third-party)
Each fact links to the page it came from; the badge says who published it (how to read sources).
- What it is SE-Asian cross-lingual semantic-retrieval memory vendor
- What it does & what's distinct SEA-LION-Embedding (March 2026): retrieval + reranking models contrastively trained on 2… vendor
- Claims / benefits SOTA on SEA-BED for Burmese, Filipino, Indonesian, Khmer, Malay, Lao, Tamil, Tetum, Thai… vendor
- Modalities text vendor
- Created 2023 (first SEA-LION launch) third-party
- Funding Nationally funded (Singapore government / AISG); no private venture funding vendor
- Customers / scale 50-200 ppl Southeast Asian research community, non-commercial vendor
- Pricing Free download (Hugging Face + AISG website); no commercial pricing vendor
- Compliance IBM MOU for AI governance integration; AISG plans compliance/risk frameworks third-party
- Data handling National research project; public data; no commercial data handling vendor
- Deployment Both (free download self-hosted + Amazon SageMaker JumpStart for managed deployment) vendor
- HQ Singapore vendor
- Founders / pedigree AI Singapore (AISG) — national research foundation; no individual founders listed vendor
- Memory volume / scale 245M training pairs; 128K-token context (no memory-volume claim) vendor
- Versioning none vendor
- Schema evolution schema with migration vendor
- Namespace primitives per-tenant vendor
- MCP support not supported vendor
- A2A support not supported vendor
- Import / export Hugging Face checkpoints registry
- Integration count 0 vendor
- Orchestration agnostic vendor
- Programmatic control read-only API + HF download vendor
- Vendor benchmarks SOTA on SEA-BED for 10 SEA languages (vendor) vendor
- Pricing specifics OSS only (free download; HF + AISG) vendor
- Validated verticals SE Asian government, public sector, multilingual enterprise vendor
- Time to running <1hr (HuggingFace + sample data) registry
- Anti-fit not for English-monolingual use cases (English-first models perform better) vendor
- Optimised for SE-Asian language coverage (10 languages, contrastively trained) vendor
- Adjacent infrastructure self-hosted; or use any embedding pipeline registry
- Pros First Southeast-Asian-language-tuned memory model; strong with Bahasa, Thai, Vietnamese. vendor
- Cons Regional scope limits global relevance; smaller English benchmarks coverage. vendor
- Project & sources sea-lion.ai vendor
- cost-input-usd-per-mtok 0 vendor
- cost-output-usd-per-mtok 0 vendor
- cost-tier free vendor
- cost-pricing-model free-tier vendor
- cost-last-verified 2026-06-29 vendor
- architecture-deployment-locus hybrid vendor
- licensing-bucket commercial vendor
- positioning-platform-vs-product platform vendor
- taxonomy-three-layer-rollup agent-infra repo