Companies · AI / ML
San Francisco · CA, USA · AI / ML · founded 2026 · https://www.trykinect.ai/
Diligence memoA one-page analyst read on Kinect — recommendation, valuation, rhythm, risks.→Kinect: limited disclosed financing to assess.
Synthesized from the figures below est. — every claim rests on a number shown on this page.
Kinect 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”
The AI-Native Commerce Stack
Kinect builds AI agents that know your brand, your catalog, and your customers. On your site, they sell every visitor — running the conversation, adapting product pages in real time to each customer segment, picking the right recommendation for the question being asked. The agent picks up on what each shopper actually wants from how they ask, what they hesitate on, what they compare, and what objection makes them bounce. We take all of a brand's data and make a structured catalog, brand voice, fit notes, return reasons, segment-level nuance — all so the Kinect agents truly can speak about a brand. When an agent describes the brand, the version it describes is the one you'd want them to, not whatever it guessed from a public catalog scrape. We expose this data as well in the form of agent storefronts, letting every other AI talk about your brand in the way you would want too. We're building for human shoppers today and the AI agents that shop and discover for them. Either way, the entire website needs to get a lot smarter and personalized. Two surfaces. One layer. Built for scaling DTC ecommerce brands.
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.
Kinect 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 |
|---|---|---|---|---|---|
| a0.dev | AI / ML | — | — | — | same sector |
| Accord | AI / ML | — | — | — | same sector |
| Acely | AI / ML | — | — | — | same sector |
| Adam | AI / ML | — | — | — | same sector |
| Aedilic | AI / ML | — | — | — | same sector |
| Affogato AI | AI / ML | — | — | — | same sector |
| Aftercare | AI / ML | — | — | — | same sector |
| Afternoon.co | 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 |
|---|---|---|---|---|
| Channel3 Database of every product on the internet | AI / ML | — | — | 80% |
| Senso Control what AI says about you | AI / ML | — | — | 79% |
| Anglera AI-Powered Product Data Enrichment | AI / ML | — | — | 79% |
| Closera AI Shopping Agent for Your Ecommerce Store | AI / ML | — | — | 79% |
| Promoted.ai Dramatically better search and ads for marketplaces | AI / ML | — | — | 78% |
| item The AI-Native CRM that works for you | AI / ML | — | — | 78% |
| Wildcard AEO/GEO for E-Commerce and Retail | AI / ML | — | — | 78% |
| Salesforce Com Inc Salesforce is the #1 Agentic AI CRM, helping companies become Agentic Enterprises where humans and agents drive success together through a unified AI, data, and Customer 360 platform. | AI / ML | Growth/Late | $28.3B | 78% |
See where Kinect sits in the wider market — its sector, location and stage cohorts, each with their own leaderboards and capital-flow timelines.
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