Sailor Search is an AI-native search API for agentic systems and research workflows. The system centers on predictable API behavior, source-aware results, clean markdown output, and data shaping that keeps downstream LLM workflows efficient.
The Product Contract
Search APIs for agents need to do more than return links. They need to provide structured evidence, clean extracted content, and enough metadata for another system to judge source quality.
The backend contract was designed around predictable responses: clear result shape, source-aware fields, extraction status, and compact content that can be passed into RAG and research flows without wasting context.
What I Worked On
- Designed backend and infrastructure for an AI-native search API.
- Implemented clean markdown output, deep search, enrichment, and token compression.
- Built foundations for predictable API behavior and production search workflows.
Durable Shape
The important decision was to optimize for downstream reasoning instead of human browsing alone. Clean markdown, compact context, and explicit source metadata made the API easier for agents to inspect, cite, compress, and recover from.
That made the system feel less like a search wrapper and more like a retrieval surface built for production AI workloads.