Long Arc Studios builds controlled AI software designed for complex, high‑stakes tasks that must remain understandable as they evolve. Their product, North, creates a local “proof graph” that links scattered artifacts—profiles, files, notes, code, screenshots—into an inspectable structure of claims, context, decisions, risks and gaps, enabling operators to maintain clear boundaries while the work progresses. Users can then generate workstream reports, founder packets, client briefs, investor updates, or private proof packs directly from the evidence.
Funding
Funding not disclosed
Founders
Product
Problem
Serious, knowledge‑intensive work often becomes fragmented across multiple tools—profiles, files, code repositories, notes, and screenshots—making it difficult for operators to track the logical flow, maintain clear boundaries, and preserve evidence of decisions and risks.
Solution
Long Arc Studios offers North, a controlled AI‑enabled platform that consolidates these disparate artifacts into a local “proof graph.” The proof graph structures information into claims, context, decisions, risks, and gaps, providing an inspectable view that preserves the thread of work. By keeping the proof graph on the operator’s device, North ensures data remains under the user’s control while AI agents can assist without losing continuity. The platform enables users to generate structured outputs such as workstream reports, founder packets, client briefs, and investor updates directly from the organized evidence. This approach maintains clear responsibility through a minimal role model and governed work environment, helping teams keep serious work understandable as it evolves.
Target Audience
Primary users are operators, project leads, and knowledge workers in enterprises or startups who manage complex, high‑stakes projects requiring rigorous documentation and traceability.
Features
- Local, AI‑assisted “proof graph” that links profiles, files, code, notes, and other artifacts into a unified, inspectable structure
- Automatic organization of claims, context, decisions, risks, and gaps for transparent review
- Role‑based governance model that defines clear responsibilities and preserves accountability
- One‑click generation of workstream reports, founder packets, client briefs, investor updates, and private proof packs from the proof graph
- On‑device data control ensuring sensitive information remains private while still enabling AI assistance