Self-learning Retrieval for Agents

Smart agents need needles, not haystacks.

More context is more hay, whether in the context window or the data warehouse. Antfly's self-learning retrieval finds answers in the data you already have. Query your own data in minutes.

Run your first query See What You Can Build

Keep your context layer

You bring the context. Antfly harvests it.

Data warehouses, storage buckets, PDFs, tickets: your context layer is already rich with answers. Antfly runs self-learning retrieval over it, right where it lives, and hands your agents what they need. Nothing to migrate, nothing to replace.

Quickstart

terminal

# Install and start in swarm mode (single-node, free)
curl -fsSL https://releases.antfly.io/antfly/latest/install.sh | sh
antfly swarm

# Create a table with a semantic index (embedded locally, no API keys)
curl -X POST http://localhost:8080/api/v1/tables/docs \
  -H "Content-Type: application/json" \
  -d '{
    "indexes": {
      "content_semantic": {
        "type": "embeddings",
        "template": "{{content}}",
        "embedder": {"provider": "termite", "model": "BAAI/bge-small-en-v1.5"}
      }
    }
  }'

# Insert a document (chunked and embedded automatically)
curl -X POST http://localhost:8080/api/v1/tables/docs/batch \
  -H "Content-Type: application/json" \
  -d '{"inserts":{"intro":{"content":"An agent believes what it retrieves."}}}'

# Query by meaning, with BM25 keyword matching fused in
curl -X POST http://localhost:8080/api/v1/query \
  -H "Content-Type: application/json" \
  -d '{
    "table": "docs",
    "semantic_search": "what does an agent trust?",
    "full_text_search": {"query": "content:retrieves"},
    "indexes": ["content_semantic"],
    "fields": ["content"],
    "limit": 5
  }'

Ready to scale?

Antfly Cloud

Multi-node, managed, and monitored. The same Antfly you run locally, deployed and scaled for you.

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