For a venture capital firm, the most expensive thing to waste is a partner’s time. The second most expensive thing is missing a deal because the research was wrong. Altis, a New York-based pre-seed startup, is building its business on the premise that it can solve both problems at once. The company calls itself a research infrastructure platform, a label that points at a very specific, high-stakes workflow: turning the messy, qualitative process of due diligence into a structured, repeatable system [altis.vc, retrieved 2025].
The Wedge Is Primary Research
Most venture intelligence tools are databases. Altis is taking a different path, one that is more labor-intensive and, if executed well, potentially more defensible. According to the company, its service identifies the key debates that should drive an investment committee decision for a Series A, B, or C company. It then builds out formal bull and bear cases through primary research, conducting interviews with customers, competitors, former employees, and domain experts [Harvard FAS, retrieved 2026]. This is not about surfacing data points; it’s about constructing a narrative with evidence, aiming to deliver what founder Chris Freeberg calls “trusted diligence at venture speed” [altis.vc, retrieved 2026].
Why Primary Venture Partners Wrote the Check
With no disclosed funding amount and a founding year of 2025, Altis is operating in near-stealth. Its primary public signal is its backing by Primary Venture Partners, a New York-based early-stage firm known for its operator-heavy approach. For a firm like Primary, the investment thesis likely hinges on two factors beyond the product idea itself. First, the founder, Chris Freeberg, is cited as having co-founded the company with a Midas-list investor, a detail that suggests immediate domain credibility and access to a powerful network [ZipRecruiter, retrieved 2026]. Second, the market timing. The venture slowdown has put immense pressure on fund performance, making rigorous, efficient diligence a survival tool [Crunchbase, retrieved 2026].
Navigating an Established Competitive Set
| Competitor | Primary Offering | Altis's Presumed Differentiation |
|---|---|---|
| CB Insights | Broad market intelligence & predictive analytics | Depth of primary, interview-based research vs. broad data aggregation |
| Harmonic | AI-driven sourcing and due diligence platform | Human-expert-led synthesis and narrative building [Crunchbase, retrieved 2026] |
| Rings AI | AI for private market mapping and scoring | Focus on the structured "bull/bear" output for investment committees |
Altis must prove that its methodology delivers uniquely actionable insights that generic platforms cannot. The risks here are operational and economic:
- Service scalability. Conducting expert interviews is not easily automated.
- The wedge’s durability. If the primary research proves valuable, what stops a larger incumbent from adding a similar service layer?
- Proof of workflow integration. The ultimate test is whether Altis becomes embedded in the weekly rhythm of a partner’s work.
The Ideal Customer and the Road Ahead
The ideal customer for Altis is the early-stage VC firm, likely managing a Series A-focused fund, where a small team of general partners is responsible for a high volume of deep-dive diligences. For them, Altis is pitching a force multiplier for partner time. The next twelve months will be about proving the model. Real traction will come from named customer deployments and case studies showing how an Altis report changed an investment decision.