SID-1

Retrieval, vector search and RAG · by SID AI

SID's first agentic search model, achieving 1.9x better recall and 24x faster performance, doubling embedding-only accuracy and outperforming frontier models on complex search tasks.

What it does

SID's first agentic search model, achieving 1.9x better recall and 24x faster performance, doubling embedding-only accuracy and outperforming frontier models on complex search tasks.

  • Retrieval models
  • Agentic search
  • Providing context for AI systems
  • Complex search tasks
Category
Retrieval, vector search and RAG
Users
Organizations needing retrieval and search model capabilities
Public API
Not offered

Not yet disclosed: deployment options, platforms, languages and support channels.

Product insights

Evidence for this product in each industry and task.

#4 · access data and knowledgeView ranking →

Documented feature

“Vector only @10 0.44 0.15s $0.0000098 0.2 0.45 0.65 0.85 Retrieval Performance Recall 0 60 120 180 Latency Seconds per Question 0 0.2 0.4 0.6 Cost USD per Question Traditional retrieval pipelines pre-program each step: query…”

Read product documentation
  • Vector only @10 0.44 0.15s $0.0000098 0.2 0.45 0.65 0.85 Retrieval Performance Recall 0 60 120 180 Latency Seconds per Question 0 0.2 0.4 0.6 Cost USD per Question Traditional retrieval pipelines pre-program each step: query…
    Read source · www.sid.ai ↗

Pricing

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Security and compliance

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