Launching today
Graft AI
Turn company operations into a living map for agents
69 followers
Turn company operations into a living map for agents
69 followers
Most agent tools assume clean APIs. Graft starts where companies actually work: legacy apps, internal tools, and workflows trapped behind screens. It learns how the work gets done, turns it into a living operational map, and gives agents stable tools with permissions, approvals, audit trails, and verification built in. When the underlying UI changes, Graft detects the drift and repairs the workflow without breaking the agent interface.
Operations as a map agents can walk is close to what I do per-client, structured facts an AI can't step outside of. Mine is one brand, yours is a whole company, and I suspect the hard part scales badly. How do you keep the map current when the operations change weekly?
Graft AI
@vladimir_iudin That is the hard part, so we treat the operational map like a versioned codebase, not a static knowledge graph. Every execution, exception, and employee correction is compared against the current map; changes are proposed as reviewable updates, tested in shadow mode, and only promoted after they pass verification. The map stays current because the company continuously contributes to it through normal work, instead of relying on a quarterly process-document rewrite. We're building knowledge graphs, real time data flow mechanisms, more info soon.
feels adjacent to Browser Use in spirit, just aimed at ERPs and desktop apps instead of the open web.
Graft AI
@ian_maxwell2 No actually, this is really different. We're not teaching agents how to interact, we're building an operational knowledge map of the company, how operations really work and today it is stuck in people's head as domain knowledge, we saw a shift where now anybody can contribute to a company's codebase but imagine now employees knowledge and how work is done in the company is operatable by agents consistently, this still breaks at scale today and we're solving that.
Browser Use helps an agent operate a UI, while Graft turns recurring enterprise work into versioned, policy-bound, independently verified tools that agents can call reliably without rediscovering the interface every time.
spend months trying to get an agent to reliably click though our old internal ticketing system before giving up, this is the exact problem.
Graft AI
@kyle_bennett6 Exactly. The problem is not getting an agent through the UI once, it is making the 500th run as reliable as the first. Graft learns the workflow, turns it into a stable tool like create_ticket or update_case, and verifies the result in the source system so the agent never has to rediscover that interface again.
Graft AI
Graft will be helping f500's transform their legacy applications into operational knowledge basis for agents to use. Agents can interact with their legacy software and help them transition into agent native software, this is a shift we're seeing but companies fail because the data is in people's head as domain knowledge so we're building the infra to make it operational by agents.
approvals + audit trails baked in from day one is the part that'll actually get this past an IT review, not the AI framing.
Graft AI
@hailey_brianna1 True. The AI gets attention, but approvals, least-privilege access, independent verification, and complete audit trails are what make Graft deployable inside a real enterprise. We're making it actually work in prod
Graft AI
Graft turns real company operations into a shared, continuously updated layer for agents. We've seen companies transform to the AI native era but fail in operations because of institutional knowledge, and graft solves that.