Service · Agents
An agent pipeline that compares every step against your app's real state before trusting it, and hands the task to a person when its confidence drops.
Each step is checked against the application's own records before the next one runs. In the published Walkcast run, 3 of 4 agent success claims were false, and the check caught all three.
Proof: WalkcastOnRamp re-parses every pull request its agents open and diffs the dependency graph against the base for broken edges and new cycles, retrying unresolved issues a bounded number of times.
Proof: OnRampCalls go through a fallback chain across providers, and the tests exercise that chain directly, because it is the part most likely to break.
Proof: ArchMind AIRules like tenant isolation are enforced by tests that fail the build, so they never depend on someone noticing in review.
Proof: Estate360By not taking its word for it. After each action the system reads the application's state and compares it with what the step was meant to change. If they disagree, the step fails or the task goes to a person. That is the method Walkcast measures, and its published run is linked in the case study.
LangGraph for most multi-step agents, CrewAI where role-based crews fit, Playwright when the agent has to work a browser, and plain tool calling when a framework adds nothing. The choice is made per project and written into the scope.
Two to four weeks for a scoped first version. A single automated workflow is typically ₹15,000–35,000, and a full agent product ₹25,000–60,000+. The exact price is fixed in writing before work starts.
You do. Code goes into your repository and your cloud from the first commit, with tests, logging and a handoff doc your team can run it from.
Two or three sentences about the problem is enough. I reply within one working day, and the first 15-minute call is free.