Run AI-powered market research on any product idea

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.

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 a POST /research request with your idea. The endpoint returns immediately with a job ID — research runs in the background.

string

required

Your product idea, up to 5,000 characters. Write it as you would describe it to a colleague.

string

UUID of an existing project to attach this research to. Pass null to keep it unattached.

string

default:"market"

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.

curl --request POST \
  --url https://api.manticscore.com/research \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "idea": "A mobile app that helps freelancers track time and automatically generate invoices from project notes",
    "project_id": null,
    "mode": "market"
  }'

import requests

response = requests.post(
    "https://api.manticscore.com/research",
    headers={"Authorization": "Bearer <token>"},
    json={
        "idea": "A mobile app that helps freelancers track time and automatically generate invoices from project notes",
        "project_id": None,
        "mode": "market",
    },
)
print(response.json())

Response 202 — new job queued:

{
  "job_id": "a1b2c3d4-...",
  "status": "queued",
  "position": 0
}

Response 200 — cache hit (identical idea already analyzed):

{
  "job_id": "a1b2c3d4-...",
  "cache_action": "clone",
  "status": "completed"
}

Use an Idempotency-Key header to safely retry the request without starting duplicate jobs.

Streaming progress events

Once you have a job_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.

curl

curl --request GET \
  --url 'https://api.manticscore.com/research/a1b2c3d4-.../events?cursor=0' \
  --header 'Authorization: Bearer <token>'

Each line of the stream is a JSON object:

{"v": 1, "event": "stage", "data": {"name": "search", "status": "completed", "queries": 12, "sources": 34, "duration_ms": 8200}}

Event types

stream_start

Emitted immediately on connection. Confirms the stream is live.

{"v": 1, "event": "stream_start", "data": {"request_id": "req_abc", "job_id": "a1b2c3d4-..."}}

stage

Emitted when each pipeline stage starts, completes, is skipped, or fails. Includes timing and counts when available.

{
  "v": 1,
  "event": "stage",
  "data": {
    "name": "analyze",
    "status": "completed",
    "duration_ms": 14300
  }
}

progress

Free-text progress messages within a stage.

{"v": 1, "event": "progress", "data": {"stage": "search", "message": "Fetching competitor pricing pages..."}}

result

Emitted once when the job completes. Contains the full research artifact.

{
  "v": 1,
  "event": "result",
  "data": {
    "job_id": "a1b2c3d4-...",
    "id": "a1b2c3d4-...",
    "idea": "...",
    "status": "completed",
    "interpretation": {},
    "incumbents": [],
    "emerging": [],
    "features": [],
    "signals": [],
    "white_spaces": [],
    "quality": {}
  }
}

done

Signals the stream is finished. Always the final event.

{"v": 1, "event": "done", "data": {}}

Checking job status

Poll the status endpoint if you prefer not to stream:

curl --request GET \
  --url https://api.manticscore.com/research/a1b2c3d4-.../status \
  --header 'Authorization: Bearer <token>'

import requests

response = requests.get(
    "https://api.manticscore.com/research/a1b2c3d4-.../status",
    headers={"Authorization": "Bearer <token>"},
)
print(response.json())

{
  "status": "completed",
  "pipeline_stage": "priorities_picked",
  "last_event_seq": 15
}

The job transitions to completed when the research-side DAG terminates at the pick-priorities stage. At that point pipeline_stage is set to priorities_picked in the same update that flips status to completed. Until then, polling clients see status: "running" with an earlier pipeline_stage. Auto-plan-build runs as the build phase after this point and does not delay the completed transition.

Research result shape

Once completed, the result contains the following top-level fields:

string

required

UUID of this research job.

string

required

The original idea text you submitted.

string

required

Final status: completed or failed.

object

Structured parse of your idea: problem statement, target user, product type, and market category.

array

Established competitors in the space, each with name, description, key features, and positioning.

array

Newer or smaller players that are gaining traction but haven’t reached scale.

array

Features that matter in this market, ranked by prevalence and strategic importance.

array

Recent market signals: funding rounds, product launches, hiring trends, press coverage.

array

Gaps and underserved opportunities identified from the competitive landscape.

object

Quality scores and a go/no-go recommendation based on market characteristics.

Additional actions

Compare with a previous version

curl

curl --request GET \
  --url https://api.manticscore.com/research/a1b2c3d4-.../diff \
  --header 'Authorization: Bearer <token>'

Returns a structured diff showing which competitors, features, and signals were added or removed since the previous research run on the same idea.

Get remix suggestions

curl

curl --request POST \
  --url https://api.manticscore.com/research/a1b2c3d4-.../remix \
  --header 'Authorization: Bearer <token>'

Returns three adjacent pivot ideas based on your completed research — useful when you want to explore related opportunities without starting from scratch.

Set reuse scope

Control whether your research can be used as a cache source for other users:

curl

curl --request PATCH \
  --url https://api.manticscore.com/research/a1b2c3d4-.../scope \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{"reuse_scope": "public"}'

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

If you hit the rate limit, your request may be captured to a retry queue rather than dropped. ManticScore will attempt to run it when capacity frees up.

Get Started

Core Features

Integrations

Real-Time Streaming

Account & Settings

Run AI-powered market research on any product idea

How the pipeline works

Starting a research job

Streaming progress events

Event types

Checking job status

Research result shape

Additional actions

Compare with a previous version

Get remix suggestions

Set reuse scope

Limits and credits

​How the pipeline works

​Starting a research job

​Streaming progress events

​Event types

​Checking job status

​Research result shape

​Additional actions

​Compare with a previous version

​Get remix suggestions

​Set reuse scope

​Limits and credits

How the pipeline works

Starting a research job

Streaming progress events

Event types

Checking job status

Research result shape

Additional actions

Compare with a previous version

Get remix suggestions

Set reuse scope

Limits and credits