Companies · AI / ML
San Francisco · CA, USA · AI / ML · founded 2023 · https://double.bot
Diligence memoA one-page analyst read on Double – Coding Copilot — recommendation, valuation, rhythm, risks.→Double – Coding Copilot: limited disclosed financing to assess.
Synthesized from the figures below est. — every claim rests on a number shown on this page.
Double – Coding Copilot is one of 2067 AI / ML companies tracked from San Francisco, CA, USA, on record since 2023. 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”
AI coding copilot engineered for performance
Do you run into these problems with Github Copilot? - Bad completions that break your train of thought when you’re writing comments? - Doesn’t close brackets, or adds too many closing brackets? - Functions, variables, and libraries not being auto-imported after accepting a suggestion? - Multi-cursor mode not working? - Wish copilot could name your variables? - Wish copilot could trigger in the middle of a line? - Want to stop wasting time with GPT3.5 chat and default to GPT4? Double is an high quality alternative to Copilot inside VS Code, engineered for performance. It’s designed with great craftsmanship by people who care a lot about getting the small details right.
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.
| Stage | Amount · real | Announced | Post-money · est | Value · est | Conf. |
|---|---|---|---|---|---|
| No rounds recorded. | |||||
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.
Double – Coding Copilot 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.
| Company | Sector | Stage | Raised · real | Value · est | Why similar |
|---|---|---|---|---|---|
| 14.ai | AI / ML | — | — | — | same sector |
| 21st | AI / ML | — | — | — | same sector |
| Absurd | AI / ML | — | — | — | same sector |
| Accord | AI / ML | — | — | — | same sector |
| Acely | AI / ML | — | — | — | same sector |
| Aemon | AI / ML | — | — | — | same sector |
| Aether | AI / ML | — | — | — | same sector |
| Affogato AI | AI / ML | — | — | — | same sector |
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.
| Company | Sector | Stage | Value · est | Match |
|---|---|---|---|---|
| Simplify Helping a billion people build their dream career | AI / ML | — | — | 74% |
| Duo AI Technologies, Inc. | AI / ML | Pre-Seed | $581K | 72% |
| Double Robotics Telepresence robots | Robotics | — | — | 72% |
| Logical A proactive desktop copilot. Clippy, but actually good. | AI / ML | — | — | 72% |
| Pierre Pierre is a new, opinionated, git platform. | AI / ML | — | — | 72% |
| PerfectBit, Inc. Correct by construction AI training data | Robotics | — | — | 71% |
| Glue The Interface Design Canvas for AI agents | AI / ML | — | — | 71% |
| b12 Labs Chemical Copilot for Pharma and Biotech | Biotech | — | — | 71% |
See where Double – Coding Copilot sits in the wider market — its sector, location and stage cohorts, each with their own leaderboards and capital-flow timelines.
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