Companies · AI / ML

MossFall 2025Active

San Francisco · CA, USA · AI / ML · founded 2025 · https://moss.dev

Diligence memoA one-page analyst read on Moss — recommendation, valuation, rhythm, risks.
Total raised · real
0
Rounds
Latest step-up
Top 39%
Sector rank · raised
Latest stage · inferred

Moss: limited disclosed financing to assess.

Synthesized from the figures below est. — every claim rests on a number shown on this page.

Where it sits in AI / ML

Moss is one of 2067 AI / ML companies tracked from San Francisco, CA, USA, on record since 2025. 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

Real-time semantic search for Conversational AI

Moss is building the real-time semantic search runtime for conversational and multimodal AI. Our system enables voice agents, copilots, and chat interfaces to retrieve, reason, and respond in sub-10 ms, delivering the responsiveness that makes AI interactions feel truly natural. If you’ve ever built a conversational or voice AI product, you’ve felt the lag. That moment when an agent pauses and the illusion of intelligence breaks. The bottleneck is almost always retrieval. Each query hops across networks and databases, adding delay and cost. Moss eliminates that gap by keeping retrieval close to where the agent runs. Moss runs natively across browsers, mobile devices, and servers with an optimized vector index built in Rust and WebAssembly. It enables teams to build AI products that feel instant, contextual, and adaptive. The experiences that sustain engagement and unlock new kinds of interaction. For our customers, this translates into tangible business value: stronger user retention, higher conversion, and entirely new product categories made possible by real-time understanding. Moss is already powering production pilots across voice AI and developer platforms, achieving sub-10 ms retrieval and 70–90% token savings compared to traditional pipelines.

Artificial IntelligenceDeveloper ToolsSaaSai/ml
Find Moss online

As reported in public records reported — not modeled.

US
Jurisdiction
Amount raised vs valuation, by round

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.

Financing ladder & sequence gaps

No staged rounds to sequence.

Modeled valuation trajectory
Base estimate est.
Conservative case
Upside case
Modeled post-money

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.

Financing rhythm
Avg between rounds
Capital velocity
On record since
First round
0
Rounds on file
How it compares to the market

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.

Total raised — vs sector median (real $, all stages)
This company
Sector median$4.7M
Modeled value — vs sector median (estimate, all stages)
This company
Sector median$27.9M

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

Full financing history

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.

StageAmount · realAnnouncedPost-money · estValue · estConf.
No rounds recorded.
Intelligence
Modeled next raise
Modeled next size est.
Last step-up
Capital velocity

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.

Registry & provenance

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

United States
Country of record
US
Jurisdiction
Similar companies

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.

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Ai AibaAI / MLsame sector
Semantically similar

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.

CompanySectorStageValue · estMatch
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Undermind
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Biotech77%
Sophys
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AI / ML77%
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Voice data for AI
AI / ML77%
Velvet
The multimodal data lab.
77%
Semantic Ai, Inc.ComputersSeries A$146.2M77%
Fiber AI
The freshest data APIs for AI sales, recruiting, & growth products
AI / ML77%
VOYGR
Real-world place intelligence for AI apps and agents
Food & Beverage77%
Frequently asked
What does Moss do and where is it based?
Moss operates in the AI / ML sector, based in San Francisco, CA, USA. Real-time semantic search for Conversational AI
Explore related

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

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