AI-driven development lifecycle
Agents that turn source repos into test suites and audit evidence.
Claude Code agents connected to Jira, Confluence and GitLab over MCP read the application code, generate test cases and runtime data, and produce rule-level traceability that holds up in audit.
Repo + Confluence→
Claude Code agent→
Tests + data→
Evidence
Developer platform
A Playwright framework teams adopt.
Page objects, data-grid helpers, environment configs, DB fixtures, CI templates. Now the team standard.
import { test } from './fixtures';
test('report ready', async ({ grid, db }) => {
await grid.filter({ status: 'Final' });
await db.expectRows('report', 1);
});
// fixtures: env, DB, grid helpers
Agentic ops
Natural-language control of services, jobs and pods.
An MCP server over an internal Spring Boot API so one request can chain restarts, Autosys jobs and OpenShift checks across environments.
prepare the UAT environment and check pod health
Done. services restarted · 3/3 pods healthy · data refresh job queued
Release engineering
Regression from six hours to forty-five minutes.
A parallel-execution platform across SIT, UAT and pre-prod that made same-day release-candidate validation routine.
Performance tooling
Load tests generated from the real system.
Swagger specs and recorded user flows become Karate-Gatling simulations, so performance tests track the API rather than a hand-written guess.
Swaggeror HAR capture
→
GeneratorKarate features
→
Gatlingsimulation
Data validation at scale
Reusable reconciliation utilities for millions of records.
A library of recon and validation utilities that compare datasets across AWS Athena, Oracle and MSSQL, recompute expected results independently, and check generated Word, PDF and Excel outputs. Millions of rows reconciled in hours, with row-level diffs as evidence.
Athena12.4M rows
⇄
SQL12.4M rows
0 mismatches · 1h 52m