How We Match You With Investors
Our hybrid matching system combines structured data analysis with AI to identify the venture capital funds most likely to invest in your company. Here's how it works.
1 Eligibility Filter
Every fund in our database has a profile built from its website, SEC filings, and public disclosures. We start by filtering out funds that don't invest in your stage or sector — there's no point ranking a seed-stage SaaS company against a growth-stage biotech fund.
A fund must match on both criteria to advance:
| Criterion | What We Check |
|---|---|
| Investment Stage | Your funding stage (Early, Growth, or Late) must align with the fund's stated stage preferences. |
| Primary Sector | Your sector (e.g., Enterprise SaaS, Healthcare, Fintech) must appear in the fund's focus areas, drawn from our 20-category taxonomy with 211 keywords. |
Affinity Filter
Some funds have specific affinity requirements — for example, they invest exclusively in women-founded or underrepresented-founder-led companies. If a fund has such a requirement and your founding team doesn't match, that fund is removed from consideration. Funds without affinity requirements are unaffected.
2 Weighted Scoring
Funds that pass the eligibility filter receive a base score of 15 points and are then evaluated across multiple dimensions. Each factor adds points based on how well you align with the fund's investment thesis, up to a combined cap of 85 points.
| Factor | Max Points | How It Works |
|---|---|---|
| Sector Depth | Up to 15 | Rewards funds that specialize in your sector. For life sciences, we go deeper — checking for specific expertise indicators like clinical trial experience, drug development, or genomics focus rather than just sector labels. |
| Geography | Up to 10 | Awards points when your company is in the fund's stated geographic investment focus, or when both you and the fund are in the same US region (e.g., both Northeast or both West Coast). Global funds with no geographic restrictions receive a partial bonus. No points are awarded if there is no geographic overlap. |
| Business Model | Up to 15 | Checks whether the fund has experience with your business model (B2B, B2C, SaaS, marketplace, D2C, etc.) based on their investment keyword profile. |
| Subsector Keywords | Up to 25 | Matches your specific subsector keywords (e.g., "supply chain," "developer tools," "clinical trials") against the fund's keyword profile using fuzzy matching. Each keyword match contributes one-fifth of the maximum points, so you need about 5 matching keywords to reach the full value. |
| Technology Alignment | Up to 20 | Matches your technology stack (AI/ML, blockchain, IoT, etc.) against fund interests. For life sciences startups at generalist tech funds, the technology bonus is reduced to avoid misleading rankings. |
3 Advanced Ranking
The top-scoring funds from Step 2 are then evaluated on relationship and risk factors that go beyond thesis alignment. This step can add up to 20 bonus points or apply significant penalties.
Bonus Factors
| Factor | Details |
|---|---|
| Shared Backgrounds | If you attended the same school or worked at the same company as someone at the fund, that's a relationship signal. Recent graduates from the same school get a stronger bonus than older alumni ties. Points are multiplied by the person's seniority — a shared background with a General Partner matters more than with an Analyst. |
Penalty Factors
| Factor | Penalty | Details |
|---|---|---|
| Competitor Conflict | -50 | If a fund has already invested in any of your direct competitors, a flat 50-point penalty is applied regardless of how many competitors are found. We check the fund's portfolio when a portfolio page URL is available. |
| Fund Inactivity | -5 to -30 | Based on the fund's most recent SEC Form D filing, a penalty ranging from 5 to 30 points is applied to funds with older filings. More recent filings receive smaller penalties while significantly outdated filings receive larger ones. No penalty is applied for filings within 3 years or when no filing date is available. |
| Fund Size Mismatch | -15 | Raising a small round from a very large fund (or a large round from a small fund) signals a poor fit. A penalty is applied when there's a meaningful mismatch between your raise amount and the fund's typical check size. |
4 AI Strategic Fit Analysis
After traditional scoring produces an initial ranking, our AI layer evaluates the top matches for strategic fit — the kind of nuanced alignment that rule-based scoring can miss.
For selected top-ranked candidates, we send a structured summary of your company and the fund's investment profile to an AI model. The AI evaluates:
| AI Evaluation Criteria | What It Considers |
|---|---|
| Thesis Alignment | Whether your company's problem, solution, and market fit within the fund's stated investment thesis — not just keyword overlap, but conceptual alignment. |
| Strategic Fit | How your business model, technology approach, and market positioning relate to the fund's portfolio strategy and known preferences. |
| Contextual Signals | Factors like geographic relevance, stage appropriateness, and sector depth that benefit from holistic assessment rather than individual scoring. |
The AI returns a strategic fit score (0–15 points) and a brief explanation that becomes part of your match narrative. This bonus can meaningfully re-order the top results — a fund that scored well on traditional factors but has weak strategic alignment may drop below a fund with stronger holistic fit.
AI analysis is applied only to the highest-ranked matches (not the entire database) to keep results focused and costs manageable. If AI analysis is temporarily unavailable, your matches are still generated using the full traditional scoring system.
5 Read the fit landscape
Results are shown on a two-axis fit map rather than reduced to public match tiers. The horizontal axis is Match Strength: how closely your company matches this fund’s investment targets. The vertical axis is Percentile Rank: how that match compares with other funds in the Atlas investing in companies at the same stage and in the same sector.
| Direction | Interpretation |
|---|---|
| Right | A closer match with the fund’s investment targets. This is not a probability of investment. |
| Up | A stronger comparison with other Atlas funds investing in companies at the same stage and in the same sector, with Top 5% at the top of the map. |
| Position unavailable | Legacy results or incomplete source data may not have enough information for either coordinate. They remain visible with an honest unavailable state. |
AI is applied only where calculated for a match. When it is unavailable, the composite remains grounded in the traditional scoring and evidence shown in the report.
Where Our Data Comes From
Our fund profiles are built from multiple public sources:
- Fund websites — crawled and analyzed using natural language processing to extract sector focus, stage preferences, and geographic coverage.
- SEC Form D filings — parsed from EDGAR to determine fund activity, filing recency, and raise amounts.
- Team profiles — assembled from fund team pages and LinkedIn data to identify key decision-makers and their backgrounds.
- Portfolio pages — scraped to identify existing portfolio companies and detect potential competitor conflicts.
All scoring is transparent. Each match includes a breakdown of the factors that contributed to its ranking, so you can see exactly why a fund appeared in your results and make informed decisions about where to focus your time.