DAGWorks Inc.Winter 2023Acquired☆Watch⊞Compare

DAGWorks Inc. is one of 2067 AI / ML companies tracked from San Francisco, CA, USA; Remote, 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”

Open source tools & services for reliable AI Agents & AI Applications

We’re on a mission to enable everyone to build reliable AI agents & AI applications. We're fully open source, and provide a unique integrated development & observability experience for those building anything in the AI space. This is the first step towards laying the foundations for Composable AI Systems; all AI systems need observability and introspection to be first class for them to be reliable. How? We're standardizing how people write python to express data, ML, LLM, & agent workflows/pipelines/applications with lightweight frameworks. So that no matter the author, it'll be easy to collaborate, connect, and importantly in one line integrate observability and datastore needs. This speeds up time to production and reduces TCO because code remains easy to maintain and your data flywheel stays manageable. So you can increase the top line & bottom line of your business by delivering on AI that is reliable. We've got two open source projects: - one focused on AI applications, called Burr (https://github.com/dagworks-inc/burr). - one focused on AI pipelines/workflows, called Hamilton (https://github.com/dagworks-inc/hamilton) see https://www.tryhamilton.dev Both Hamilton & Burr come with self-hostable UIs (+ enterprise & SaaS offerings). With a one-line code change, you get versioning, lineage / tracing, cataloging, and observability out of the box with Hamilton. With Burr you get tracing, observability and persistence in a single line addition.

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.

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

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