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.
At a glance
- Type
- SE-Asian cross-lingual semantic-retrieval memory
- Tier
- T2
- Section
- Dedicated memory layers
- Created
- 2023 (first SEA-LION launch)
- Latest release
- not applicable — not OSS
- License
- not applicable — not OSS
- GitHub
- not applicable — no GitHub repo
- Pricing
- Free download (Hugging Face + AISG website); no commercial pricing
- Funding
- Nationally funded (Singapore government / AISG); no private venture funding
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
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.