Applied AI for enterprise revenue teams.

An email, CRM update, or proposal is one step in a deal. Over a long cycle, the account changes, new stakeholders enter, requirements move, and earlier decisions still constrain what can happen next.

Today's agents can complete each step in isolation and still fail to carry forward what the earlier work established. We build agents that keep the current goal, history, decisions, and next action together as the deal moves.

Revenue context is spread across calls, CRM records, messages, documents, support, product, and finance systems. Salesgraph connects those records around the account, opportunity, buying process, and approvals.

The agent retrieves evidence for the current decision and retains what changed. People can review each action and keep control of pricing, contracts, and customer commitments.

A buyer may add a reviewer, revise a requirement, delay a decision, or return after weeks. The agent needs to update the plan, complete the next work, and resume later without restarting from the CRM record.

The work between those decisions depends on the current plan. Salesgraph carries that plan forward after each wait. The account team stays responsible for the buyer relationship.

A closed win and a closed loss are useful labels, but neither explains what happened. The buying group, sequence of approvals, long gaps, and buyer actions around the deal provide the evidence needed to review the result.

A reviewed outcome becomes part of the context used to evaluate later agent work. It can change which deal history is retrieved and which risks are checked.

Time saved on a document is useful, but it does not show whether the agent advanced the deal. We evaluate its work against observable buyer decisions, stage changes, wins, renewals, and expansion.

The execution history ties the agent's work to the deal trajectory and commercial result. It does not claim which action caused the outcome.