Doe Labs · Jul 2026
Doe announced website publishing, a Word editor, and memory improvements, signaling continued product expansion for enterprise workflow automation.
Public company, workplace, funding, and market signals
Updated Jul 30, 2026
Doe is a San Francisco-based AI platform for work / agent cloud that connects to company systems and executes multi-step workflows, returning sourced artifacts and receipts. Official YC and product pages place the company in 2025; one pricing page says 2024, but the broader official record is 2025.
Primary product
AI platform for work that acts as an action engine / agent cloud for executing business workflows across connected tools
Founded
2025
Headquarters
San Francisco, California, United States
Team size
11-50
Industry
Software
Sub-industry
Enterprise AI agents / workflow automation
Offices
0 jobs at Doe
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Business model
Stage
pre-seed
Total raised
$500K
Latest round
Pre-Seed · Sep 2025
Latest amount
$500K
Sep 2025
Investors
Execution-heavy, high-velocity culture focused on shipping useful work quickly, with repeated emphasis on accountability, security, auditability, and measurable output rather than chat-centric AI.
Compensation
Public job pages emphasize high standards, startup experience, and fast-tracked applications for standout builders. A third-party Built In listing showed a Systems Engineer role at $100k/year, but Doe’s own careers page does not publicly disclose a full compensation or benefits package.
Pricing
Publicly listed plans are subscription-based and usage/credit-based, with team pricing starting at $500 per user per month and custom enterprise pricing.
Differentiators
Technology
Customers
Competitors
Estimated revenue
~$2.3M ARR (GetLatka estimate, Sep 2025)
Doe Labs · Jul 2026
Doe announced website publishing, a Word editor, and memory improvements, signaling continued product expansion for enterprise workflow automation.
Doe Labs · Jun 2026
A product strategy post emphasizing company-native agents, governance, and the need for useful work rather than raw model output.
Doe Labs · May 2026
A positioning post that frames Doe around increasing useful output per employee rather than just chat interactions.
Doe Labs Research Team · Apr 2026
A use-case page showing Doe applied to competitor monitoring, market sizing, and funding/M&A tracking.
Doe Labs · Feb 2026
Doe compared itself with OpenClaw, arguing its differentiator is enterprise security, scalability, and team-ready governance.