Product Reports Resources Pricing Login Book a demo

Cookbook 07 · Startup sourcing

Spot the next raise

Screen for fundraising timing, then add enough company evidence to decide who deserves research now.

Python 15 minutes 3 API calls Intermediate
python find_next_round_candidates.py Queue built
GET /data/companies

signal_timing[gte] = 70
signal_team[gte] = 50
sort = -signal_rating

Loading the real candidate queue...

12candidates shown
11companies hiring
122open roles

The goal

Turn a broad market into a timely research queue

A sector search tells you who exists. It does not tell you which companies warrant attention this week. Dealroom Signal adds a timing screen, while company records add context for the analyst reviewing the result.

Find operational European climate-tech startups founded since 2019, with $1M to $50M in total funding, that pass Dealroom Timing and Team signal thresholds.

The output is a sourcing queue, not a forecast. Its job is to focus research on a manageable set of companies with stronger current signals.

terminal
python -m venv .venv
source .venv/bin/activate
pip install requests python-dotenv

Store DEALROOM_CLIENT_ID and DEALROOM_CLIENT_SECRET in a local .env file. Keep it out of version control.

Use Timing to screen, not to promise

The Timing component of Dealroom Signal measures how likely a company is to raise its next round soon. The Team component captures founder and team evidence. Both accept numeric filters from 0 to 100.

FilterRole in this workflow
signal_timing[gte]:70Requires a stronger next-round timing signal
signal_team[gte]:50Removes companies with a weak Team component
signal_ratingReturns an overall Signal score for ranking and review

Important response detail

The company list can filter on Timing and Team components, but company records return the overall Signal score. Preserve the thresholds with the saved query instead of presenting unavailable component values.

Keep the screen commercially useful

Resolve readable labels through the reference endpoints, then constrain stage, geography, operating status, age, and prior funding.

Climate TechSector · 2181301
EuropeHQ location · 34
$1M to $50MTotal funding

The upper funding bound keeps later-stage companies from dominating the queue. Current headquarters defines Europe in this example.

Combine the constraints in one company query

find_next_round_candidates.py
company_filter = "and(" + ",".join([
    "tag_id[eq]:2181301",
    "hq_location[eq]:34",
    "is_startup[eq]:true",
    "company_status[eq]:operational",
    "launch_date[gte]:2019",
    "total_funding[gte]:1000000",
    "total_funding[lte]:50000000",
    "signal_timing[gte]:70",
    "signal_team[gte]:50",
]) + ")"

Use GET /reference/filters/search and GET /reference/filters/location/values to resolve the tag and location IDs. The downloadable script does both before requesting companies.

Rank the screened cohort by overall Signal

Once every result has passed the component thresholds, sort by the overall Signal score. Ask for a wider pool, then show a concise queue.

find_next_round_candidates.py
payload = client.get(
    "/data/companies",
    {
        "filter": company_filter,
        "sort": "-signal_rating",
        "limit": 50,
        "include_total": "true",
        "currency": "USD",
    },
)

candidates = rows(payload)[:12]

Retain the returned funding, headcount growth, hiring status, and open roles. These fields help an analyst challenge or strengthen the initial timing screen.

Real output

Inspect the next-round research queue

Every company shown passed the Timing and Team thresholds in the saved query.

JSON

Loading the candidate queue...

Snapshot generated from the Dealroom API. Re-run the script for a current queue.

Research the company before acting on the signal

Signal helps decide where to look first. It does not establish that a company is fundraising, needs capital, or fits your investment thesis.

  • Confirm sector fit beyond the taxonomy label.
  • Review the latest funding round and estimate runway separately.
  • Check whether headcount growth reflects expansion, recovery, or a small base.
  • Validate hiring activity and leadership changes from primary sources.
  • Use direct company evidence before making contact or recording a fundraising claim.

Complete example

Download the candidate-queue generator

The file includes OAuth2 authentication, bounded retries, taxonomy resolution, reusable thresholds, Markdown output, and structured JSON.