Deal-Sourcing & Signal Platform
A scoring pipeline that complements PitchBook and Affinity — ingests startup-database structured data plus unstructured signals (technical hiring, GitHub activity, product launches, supplier-relationship graph), applies your fund's thesis-specific scoring, and feeds your CRM weekly.
- Engagement
- 6–10 week build · weekly CRM refresh
- Built for
- Partners · Associates · Sourcing teams
PitchBook and Affinity are excellent at the universe and the CRM. The work is the ranking layer in between — your fund's thesis encoded as scoring rules, the alt-signals PitchBook misses (hiring deltas, GitHub commit velocity, product-launch tracking), and the weekly refresh.
What this is
A scoring layer on top of the universe data your fund already pays for. Three layers:
- Multi-source ingestion. Structured data (PitchBook, Crunchbase, sector-specific databases), unstructured signal layers (hiring, GitHub, product launches, partnership graph). Normalized into a unified company graph with daily delta tracking.
- Thesis scoring. Per-vector weighting tuned to the fund's thesis. Sector-specific configurations where the fund's mandate spans distinct sectors.
- CRM hand-off. Weekly top-tier delivery with signal context. The partner sees the score AND the reasons.
How it's built
Same data infrastructure as Sector Mapping Engine and Founder Network Intelligence — they're three products on a shared signal layer with different unit-of-observation. CRM integration via Affinity / DealCloud / Attio APIs.
What you get
- Per-vector signal coverage with documented data sources.
- Per-thesis scoring weights, versioned.
- Weekly top-tier delivery into your CRM with signal context.
- Per-company drill-down to the underlying signal trajectory.
- Quarterly weight-review with the partners.
Engagement is shape, not list.
Length and price are functions of the data and the destination. The shape below is the typical engagement.
- Length
- 6–10 week build · weekly CRM refresh
- Lead
- Bogdan
- Cadence
- Async, weekly
- Bar
- Production
Scoped during the discovery call against the actual data and the operation it integrates with.
Principal engineer. Architecture and most code ships through one keyboard.
Written updates between, calls when the decision needs the room.
Async correctness, capacity under burst, observability at every boundary.
Products this composes with.
Same suite, or vertical-specialized versions in another.
- Same suite · Venture Capital Suite
Founder Network Intelligence
A people-level tracking layer — monitors departures from a curated 'talent watchlist' of notable companies, surfaces clusters and individuals to the partners with context (role, tenure, who they worked with), refreshes daily.
- Same suite · Venture Capital Suite
Sector Mapping Engine
An auto-updating sector mapping platform — landscape diagrams with company-activity signals (funding, hiring, product launches, supplier-customer mention graphs) refreshing daily, navigable from sector down to individual company.
- Same suite · Venture Capital Suite
Startup Evaluation Engine
A packaged evaluation report per deal — automated financial-model review and cap-table analysis, founder-background research with structured outputs, market-size triangulation, comparable-company benchmarking. Delivered as a partner-readable document for the investment committee.
What buyers ask about this one.
Why this instead of just PitchBook's discovery tools?
PitchBook discovery is filter-based on structured data they already have. The signal vectors that matter early — technical hiring patterns, GitHub commit velocity on a public repo, supplier-customer relationship graph shifts — those aren't in PitchBook's structured fields. This product is the scoring layer for those vectors.
What signal vectors do you weight?
Technical hiring acceleration (eng team growth as a leading indicator), GitHub commit velocity on public repos, product-launch and feature-ship tracking, customer and partnership-mention graph, employee-review-trajectory. Per-engagement, the vectors are weighted to the fund's thesis.
Distinction from the Founder Network Intelligence product?
Different unit of observation. Founder Network is people-level — tracks individuals across companies and surfaces them before the new company exists. Deal-Sourcing & Signal is company-level — surfaces and ranks companies that exist. Use the founder layer for the earliest-stage thesis, the company layer for series-A-and-up.
How does it integrate with our CRM?
Affinity is the canonical case (we've shipped this most often). DealCloud, Attio, and Salesforce-based CRMs are supported. The weekly top-tier delivery posts into a configurable CRM stage with the underlying signal data attached so the partner can drill in.
Pricing?
Scoped against signal-vector coverage and CRM-integration depth. Discovery call covers both.
If the deliverable matches the gap, the next step is one call.
We'll scope length and price against your data and the operation it integrates with. No retainer, no fishing.
Bogdan and team · async-first · OP—2026