Market Research is the starting point for most work in ManticScore. You submit a plain-language product idea and the platform runs a five-stage AI pipeline — interpret, search, judge, analyze, and persist — that returns a complete competitive landscape: who already exists in the space, what features matter, where gaps remain, and how strong the opportunity looks overall. Results are cached and versioned, so you can rerun research on the same idea over time and compare what changed.Documentation Index
Fetch the complete documentation index at: https://docs.manticscore.com/llms.txt
Use this file to discover all available pages before exploring further.
How the pipeline works
Each research job progresses through five stages. You can watch them in real time by streaming the events endpoint.| Stage | What happens |
|---|---|
| interpret | The AI parses your idea into a structured problem and target market |
| search | Web searches are run to collect competitor and market data |
| judge | An LLM evaluates the quality of retrieved sources (non-blocking) |
| analyze | The collected data is analyzed into structured insights |
| persist | Results are saved and a quality score is computed |
The judge stage scores retrieval quality but never blocks a run. Even if it fails, the pipeline continues and you still receive full results.
Starting a research job
Send aPOST /research request with your idea. The endpoint returns immediately with a job ID — research runs in the background.
Your product idea, up to 5,000 characters. Write it as you would describe it to a colleague.
UUID of an existing project to attach this research to. Pass
null to keep it unattached.Research mode. Use
market for standard competitive analysis. Use feature to automatically chain into Feature Deep Research on the top 5 features once market research completes.Streaming progress events
Once you have ajob_id, connect to the events endpoint to receive real-time updates. The stream uses newline-delimited JSON (NDJSON) and supports cursor-based resume — if you disconnect, reconnect with cursor=<last_seq> to replay missed events.
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Event types
stream_start
stream_start
Emitted immediately on connection. Confirms the stream is live.
stage
stage
Emitted when each pipeline stage starts, completes, is skipped, or fails. Includes timing and counts when available.
progress
progress
Free-text progress messages within a stage.
result
result
Emitted once when the job completes. Contains the full research artifact.
done
done
Signals the stream is finished. Always the final event.
Checking job status
Poll the status endpoint if you prefer not to stream:Research result shape
Once completed, the result contains the following top-level fields:UUID of this research job.
The original idea text you submitted.
Final status:
completed or failed.Structured parse of your idea: problem statement, target user, product type, and market category.
Established competitors in the space, each with name, description, key features, and positioning.
Newer or smaller players that are gaining traction but haven’t reached scale.
Features that matter in this market, ranked by prevalence and strategic importance.
Recent market signals: funding rounds, product launches, hiring trends, press coverage.
Gaps and underserved opportunities identified from the competitive landscape.
Quality scores and a go/no-go recommendation based on market characteristics.
Additional actions
Compare with a previous version
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Get remix suggestions
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Set reuse scope
Control whether your research can be used as a cache source for other users:curl
Limits and credits
| Value | |
|---|---|
| Rate limit | 10 requests / minute |
| Credit cost | 3 credits per research job |
| Free tier | 20 credits / day |
| Max idea length | 5,000 characters |