ScopeSpring 2026Active☆Watch⊞Compare

Scope is one of 2067 AI / ML companies tracked from San Francisco, CA, USA, on record since 2026. By capital raised it ranks mid-pack (ahead of 62% of sector peers), and mid-pack by modeled valuation est..

Ranking is computed against this company's own sector cohort — reported capital is fact; valuation tiers are modeled.

AI analyst read est. — model-extracted from this company's public description, not a verified fact. 30%

operates a technology-led product inferred from public copy

Grounded in: “You are a venture analyst”

We help software companies get discovered and used by AI agents

Scope is the system companies use to measure and improve how agents discover, interact and use their product. As more products gets used through AI agents like Claude Code, Codex, Cursor, and similar agents, agents are starting to influence which tools get chosen, how they get set up, and whether they keep getting used. Most companies still cannot see that process clearly. We run real workflows across agents and show teams when the agent picks them versus a competitor, where it breaks, where docs or product surfaces confuse the agent, and what to change to get better results and a better agent experience. I started Scope after working on interpretability research for closed-source models at Princeton and later as an ML engineer in GEO/AEO. I kept seeing the same pattern: these systems were shaping real product discovery and usage, but companies had very little visibility into what the model was actually doing. We are starting with products that agents can directly interact with, especially APIs, infra products, CLIs, and MCP servers.

As reported in public records reported — not modeled.

Solid bars are reported offering amounts reported; hatched bars are the modeled post-money valuation est. — both on one shared scale so you can read raise-vs-worth at each round directly. Use the toggles to overlay data labels and the niche-peer / market average value lines.

No round amounts on record to chart.

No staged rounds to sequence.

Round size and date are reported; the stage label is inferred from round size. Valuation is modeled from stage benchmarks. Directional, not a quoted figure.

Not enough modeled valuation points to chart a trajectory.

Benchmarked against 2067 companies in AI / ML. Each bar is a median (the middle company, not an average — outliers don't skew it). Two yardsticks: real money raised (reported on Form D) and modeled value (our estimate est.). These are whole-sector medians across all stages, except the per-stage row.

Raised more than 62% of sector peers (real $). Modeled value above 62% of peers (estimate).

Stage is inferred from round size est., not reported on the filing — a round's dollar size maps to a bucket: Pre-Seed <$1.0M · Seed $1.0M–$4.0M · Series A $4.0M–$15M · Series B $15M–$40M · Series C $40M–$100M · Series D+ $100M–$400M · Growth/Late >$400M.

Predictive signals are modeled est. from this company's own cadence and step-up, plus sector benchmarks — directional, not advice. Peer set and a CSV export live in your analyst workspace.

Scope is an official record sourced from the U.S. Securities and Exchange Commission (SEC). U.S. data is aggregated from SEC Form D filings.

Nearest neighbours across the whole database — matched on sector, stage and capital scale, and on shared operators (officers or directors named at both companies in public filings). A discovery shortlist, not a valuation cohort — verify before acting, the same way modeled figures are directional.

Matched by meaning, not labels — a local language model reads each company's name, sector and description and ranks the closest in that learned space. This catches look-alikes that cross sector boundaries; the structured list above explains its matches, this one trusts the text. Directional, like every modeled signal here.

See where Scope sits in the wider market — its sector, location and stage cohorts, each with their own leaderboards and capital-flow timelines.

If you work at Scope, claim this profile or suggest a correction. We aggregate from public filings, so help us keep your description, website and links accurate.