Pariksha
pariksha - examination, a trial that decides
AI across the software testing lifecycle, from authoring to release.
Pariksha is Wayam's AI software-testing accelerator: intelligence across the development lifecycle so teams generate tests, execute them in CI, triage failures, and close coverage gaps without drowning in manual QA. It fits the tools engineers already use and keeps quality moving at release speed.
Workflow
Problem
Software teams drown in manual test authoring, brittle suites, and late defect discovery while release pressure keeps rising.
Outcome
Faster, higher-coverage testing across the lifecycle: generate, run, triage, and ship with AI in the loop.
01
Connect the stack
Hook into repos, CI/CD, and existing test frameworks.
02
Generate and extend
AI authors and expands tests from requirements, diffs, and prior failures.
03
Execute and triage
Suites run in pipeline; failures are clustered and ranked for humans.
04
Gate the release
Coverage and risk views show what is safe to ship.
Modules
Test generation
Create and expand unit, API, and UI tests from requirements and code.
Execution & triage
Run suites in CI, cluster failures, and surface the defects that matter.
Coverage & quality
Track risk, coverage gaps, and release readiness across the lifecycle.
Representative use cases
Autonomous End-to-End Regression Test Authoring for Core Banking Applications
A commercial retail bank updating its core banking web portal and mobile banking applications across bi-weekly release cycles.
Shift-Left API Logic & Business Rules Verification in Microservice Architecture
A fast-growing SaaS enterprise operating 40+ microservices communicating via REST and GraphQL APIs.
AI-Driven Visual Regression & Cross-Browser Testing for E- Commerce
A global fashion e-commerce brand operating web stores across 25 localized domains and 6 major browser engines.
Self-Healing Test Scripts & Flaky Test Elimination in Enterprise CI/CD
A logistics SaaS firm managing a large suite of 3,000+ UI automation test scripts running in continuous deployment pipelines.
Automated Synthetic Test Data Generation & PII Masking for Healthcare
A HealthTech platform processing electronic health records (EHR) and insurance claims under strict HIPAA privacy compliance.
Continuous Security & Vulnerability Fuzzing in DevOps Pipelines
A FinTech company building microservices for high-concurrency payment gateways and mobile wallet transactions.
Evidence
What Wayam can show for this entry
Curated solution design with an owner and a review date. No performance or production claim.
Allowed claims at this tier: Possible workflow, typical stack, prerequisites.
- Evidence tier
- T4 · Reference pattern
- Integration status
- Typical enterprise system
- Metric status
- Scenario only
- Evidence owner
- Not yet attached
- Validated
- Not yet attached
- Valid until
- —
- Content version
- 2026.09
Pending evidence attachment
This entry represents an enterprise architectural reference pattern. Customer benchmarks, run replays, and metric verifications are established during technical discovery.
Limitations
- Headline metrics are representative until a customer result is attached.
Representative metrics · Reference · scenario only
Lifecycle
AI in software testing
CI-native
execution & triage
These describe the intended outcome of the design. They are not measured customer results until a validated case is attached above.
Architecture & controls
Composed across the operating loop
Ingest
Connect the systems of record and read the signals the work already produces.
Covered by the platform
Reason
Ground context, score options against policy and the stated goal, draft the next step.
7 agent roles
Act
Execute an approved step in the system of record and keep the evidence.
Covered by the platform
Govern
Set policy, gate consequential actions on a named approver, and audit what ran.
3 agent roles
Pack Architecture & Agent Composition Graph
10 Composed Agents- AGT-0237
CI/CD Build Failure Diagnosis Agent
Software Engineering
- AGT-0250
Code Completion Agent
Software Engineering
- AGT-0251
Code Review Agent
Software Engineering
- AGT-0259
Security Scanning Agent
Software Engineering
- AGT-0305
Container Security Scanning Agent
Cyber
- AGT-0301
Vulnerability Prioritization Agent
Cyber
- AGT-0222
Incident Triage Agent
IT Operations
- AGT-0224
Change Risk Assessment Agent
IT Operations
Control gates
- A named approver on every consequential write-back
- Evidence and audit trail kept with every run
Capability atoms
- generative-design
- workflow-orchestration
- anomaly-detection
- risk-scoring
- system-connectors
Typical enterprise systems
Typical stack for solution design; compatibility is validated during discovery.
- ServiceNow ITSM
- Datadog
- PagerDuty
- Kubernetes
- GitHub
- Cursor
- Anthropic Claude Code
- Microsoft Sentinel
Designed for
technology, financial-services, healthcare, manufacturing
Business case
Model a Pariksha scenario with your own baseline
Three scenarios from the numbers you enter. Capacity released is time; it becomes a saving only when roles or costs are actually removed or avoided.
| Scenario | Improvement | Capacity released | Cashable savings | Net annual | Payback |
|---|---|---|---|---|---|
| Conservative | 9% | — | — | — | — |
| Expected | 18% | — | — | — | — |
| Upside | 24% | — | — | — | — |
Enter an annual volume and a baseline cost to see figures.
Illustrative planning scenario, not a guarantee. Results depend on process baseline, adoption, data quality, integration scope, controls, and deployment costs.
Pilot this
From solution design to a bounded pilot
Step 1 · 3–4 weeks
Discovery Sprint
Validate the workflow, data, controls, baseline and business case before anything is built.
Gate: Blueprint and pilot plan signed by the business owner, technical owner and Wayam.
Step 2 · 6–10 weeks
Bounded Pilot
Prove quality and value on agreed data against agreed acceptance tests.
Gate: Acceptance thresholds met on the evaluation set; go/no-go decision recorded.
Agrani · evidence pending4 Agrani candidates in this solution: Incident Triage Agent, Change Risk Assessment Agent, Test Generation Agent, SRE Runbook Generation AgentPairs well with