Doublezero

What do they actually do

Doublezero is building a developer platform for autonomous agents. The company says it will provide the pieces needed to build, run, and monetize agents: a runner interface with play/pause/rewind and human intervention, backend state and reasoning frameworks, analytics, and an integrated marketplace for discovering and charging for agents and tools (YC listing).

Publicly, the YC page is the only substantive description available. There are no public docs, API references, demos, pricing, or marketplace links, which suggests the product is in private alpha or early pilot stage rather than broadly available (YC listing).

Note: Do not confuse this company with the unrelated DoubleZero networking project at doublezero.xyz (doublezero.xyz).

Who are their target customer(s)

• Independent developers and small AI startups building autonomous agents: They spend time stitching together memory, debugging, and human‑in‑the‑loop tooling, and lack an easy way to publish or charge for their work (per the YC description).
• Product managers at small-to-midsize companies automating customer or internal workflows: They lack visibility and control over agent behavior in production, making it risky to deploy agents that need occasional human oversight or rollback (per the YC description).
• Independent creators and consultants packaging agent-based tools: They need a trusted place to list agents with payments and usage analytics to reach buyers and prove value (per the YC description).
• Engineering teams in larger companies running long‑lived, stateful agents: They struggle with agent memory, human/agent handoffs, and observability for multi-step failures (per the YC description).
• SaaS vendors or platform integrators adding plug‑in agents: They want an embeddable runtime and monetization plumbing to offer, meter, and control third‑party agents inside their apps (per the YC description).

How would they acquire their first 10, 50, and 100 customers

• First 10: Hand-pick pilots from YC/founder networks and maker communities; run invite-only trials with white-glove onboarding and daily support to get a few agents live and capture short case studies and UI demos (YC listing).
• First 50: Outreach to PMs and small engineering teams with 6–8 week pilots using templates for common workflows (support, ops) and a simple integration checklist; convert to paid by packaging analytics, role controls, and rollback/HITL guarantees, then amplify results via targeted SDR/email and webinars (YC listing).
• First 100: Open a limited public beta plus a creator marketplace alpha with self‑serve signups, a basic SDK/CLI, and simple rev‑share; drive growth via 2–3 SaaS partnerships, how‑to content/templates, and a community (Discord/GitHub) so creators bring buyers and add social proof for larger prospects (YC listing).

What is the rough total addressable market

Top-down context:

Near term, the addressable market is the subset of AI builders and SMB teams deploying agent workflows who will pay for an agent runner, observability, governance, and monetization; plus a take rate on agent marketplace transactions.

Bottom-up calculation:

Example near‑term SAM: 35k indie devs at ~$50/month (~$21M/yr) + 12k small/mid teams averaging 2 paid seats at ~$150/seat/month (~$43M/yr) + marketplace ~$100M GMV at a 15% take (~$15M/yr) ≈ ~$79M/year combined. This frames a conservative initial target that could grow with broader adoption.

Assumptions:

• Counts: ~35k indie devs and ~12k small/mid teams actively investing in agents over the next 1–2 years.
• Pricing: ~$50/month for individual creators; ~$150/seat/month average for teams with 2 seats.
• Marketplace: ~$100M GMV in early years with ~15% take rate; excludes enterprise deals and higher-seat expansions.

Who are some of their notable competitors

• OpenAI GPT Store: A large distribution channel and marketplace for user‑built GPTs, with a builder earnings program. Overlaps with Doublezero’s planned discovery/monetization layer for agents (OpenAI).
• LangChain / LangSmith: Frameworks and a hosted platform to observe, evaluate, and deploy agents, including tracing, evals, and agent deployment—directly comparable to a runner UI plus observability/ops (LangChain site, LangSmith docs).
• Microsoft AutoGen (incl. AutoGen Studio): Open‑source agent framework and low‑code UI for multi‑agent workflows with observability and event‑driven orchestration; relevant for building, testing, and debugging agents (Microsoft Research, docs).
• CrewAI: Open‑source multi‑agent framework with a managed cloud and management UI, HITL workflows, and integrations—competes for building and operating agents in production (CrewAI, docs).
• FlowiseAI: Open‑source visual platform to build agentic systems with human‑in‑the‑loop, tracing, and APIs/SDKs; overlaps with Doublezero’s builder/runner experience (Flowise, docs).