ThruWire
ThruWire connects humans and AI agents to a shared, durable model of work so they can coordinate and iterate without being tied to a single agent, harness, or factory. It also helps software companies decide what customer work their products should own, design the model and experience around it, and prove the result in functioning software.
At a Glance
- Established customer-facing SaaS companies
- Software product and engineering teams
- Teams building agentic products and AI-assisted workflows
- Data, marketing, CRM, and software organizations with recurring customer work
AI Tools by ThruWire
(1)
Foreman
Open Source Coding Agent Supervisor
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Products & Services
A working platform for shared customer work: it models goals, context, requirements, artifacts, evidence, dependencies, versions, current state, and execution lineage; agents operate between explicit checkpoints while people inspect, correct, approve, and steer the work.
A programmable surface that lets AI assistants inspect and update product-owned customer work. It exposes a versioned REST API, an MCP endpoint, and code mode/SDK-style integration, with OAuth authentication and project/version/execution identities.
Advisory work for software companies to identify the customer outcome they should own, map the full throughline of context and decisions, define the domain model and UX, and build a functioning reference experience and implementation path.
An open-source native Python asyncio runtime that independently supervises coding-agent work. It uses a fast decision model above slower coding agents, evaluates completion, requirements, tests, worker health, and human-escalation conditions, and can continue, steer, stop, retry, verify, or finish.
Market Position
ThruWire positions itself as the product-owned work layer for customer-facing AI: a durable, domain-specific model of goals, decisions, artifacts, evidence, dependencies, and outcomes that agents can advance and customers can inspect and steer. It distinguishes this layer from agent orchestration and runtime frameworks such as LangGraph and CrewAI, Claude Agent SDK/Skills, and long-context approaches, which it describes as solving execution, agent capability, or context-window problems rather than maintaining customer work across agents and time.
Leadership
Founders
Seth Rosen
Product leader and entrepreneur focused on data, enterprise software, and the product boundary. He founded HashPath and TopCoat, served in data products, AI, and developer experience leadership at Snyk, and was CEO/co-founder of TopCoat Data before its acquisition by Snyk.
Josh Rosen
Systems engineer and engineering leader. He worked at Sun and Oracle, co-founded HashPath and TopCoat with Seth Rosen, led engineering at Snyk, and built the ThruWire platform.
Executive Team
Seth Rosen
Co-founder, Product
Founded HashPath and TopCoat; led data products, AI, and developer experience at Snyk; previously CEO/co-founder of TopCoat Data.
Josh Rosen
Co-founder, Engineering
Worked at Sun and Oracle, co-founded TopCoat, led engineering at Snyk, and built the ThruWire platform.
Founding Story
ThruWire was started by brothers Seth and Josh Rosen after a shared career building customer-facing analytics, data infrastructure, developer tools, and security products. Their initial vision is to move software closer to the customer's decisions, work, and outcome by giving customer work a durable, inspectable model that can be advanced by changing humans and agents.
Business Model
Revenue Model
The company combines paid research/advisory engagements for software companies with access to its working platform and developer integration surfaces. Public materials describe advisory deliverables and production access arranged with the team; they do not publish self-serve pricing.
Target Markets
- Established customer-facing SaaS companies
- Software product and engineering teams
- Teams building agentic products and AI-assisted workflows
- Data, marketing, CRM, and software organizations with recurring customer work
- Customer-facing SaaS products that want to own more of a customer's larger outcome
- Software factories and software engineering workflows
- Marketing, CRM, data, and other recurring or evolving customer jobs
- Long-horizon work requiring durable goals, decisions, artifacts, dependencies, and follow-through
- Human-agent collaboration, review, handoffs, branching, and iterative work
- Building customer-facing applications from structured work such as meeting and conversation data