Plan & design
Translate product intent into architecture context, constraints, acceptance criteria and risk.
THE AGENTIC SDLC · PLAN TO PRODUCTION
One engineering
lifecycle.
Governed by evidence.
Shyena connects coding agents, test engineering, security checks and release controls into one governed workflow—from planning and implementation through production feedback. Move beyond isolated agents and bots without losing traceability, policy boundaries or accountability for the release decision.
Predictive MLGenerative AIData pipelinesComputer visionRAGDocument AIAPIsAI agentsCI/CDProduction monitoring
Illustrative workflowSAMPLE OUTPUT
$ shyena sdlc inspect --change <id>
--:--planIntent and acceptance criteria resolved
--:--buildCoding-agent change linked to repository diff
--:--testImpacted journeys selected and verified
--:--securePolicy and trust-boundary checks evaluated
--:--releaseEvidence assembled; release policy applied
--:--learnProduction signals feed the next cycle
PLAN · CODE · TEST · SECURE · RELEASE · OPERATE
The autonomous engineering loop
Plan. Build. Verify. Ship. Learn.
Connect the work that coding agents do to the checks that prove it is safe to ship. Teams define outcomes, constraints and release policy; agents and existing tools can carry out bounded work while evidence and approval requirements remain explicit.
Code & integrate
Bring coding agents, repository changes, contracts and engineering tools into one traceable workflow.
Test & evaluate
Select impacted checks, execute browser and API journeys, and verify intended outcomes.
Secure
Challenge dependencies, permissions, policies, agent tools and trust boundaries before release.
Release
Assemble evidence, apply policy gates and keep required human approvals explicit.
Operate & learn
Feed incidents, telemetry and regressions back into the next engineering cycle.
The Shyena product suite
One Agentic SDLC. Four connected capabilities.
Nexus, Vera, Chakra and Govern connect system understanding, verification, security and release evidence. They are the assurance foundation around the wider engineering lifecycle—not four disconnected testing utilities.
01Nexus
Discover & plan
Build a system-aware map of AI models, data pipelines, applications, dependencies, workflows and risk. Nexus turns product context into an executable assurance plan.
- Journey discovery
- Dependency mapping
- Impact analysis
- Autonomous test planning
02Vera
Evaluate & verify
Evaluate model outputs, predictions, generated content and end-to-end workflows against expected outcomes—not just whether a response looked plausible.
- Model and output evaluation
- Deterministic checks
- Semantic evaluation
- Workflow and outcome validation
03Chakra
Attack & break
Probe AI systems for adversarial inputs, model weaknesses, data exposure, unsafe actions and trust-boundary failures before they reach users.
- Adversarial scenario generation
- Model and input robustness
- Data exposure checks
- AI security regression
04Govern
Prove & release
Turn every test run into traceable engineering evidence. Governance is the downstream evidence layer — not the reason to start testing.
- Release verdicts
- Evidence chain
- Requirement traceability
- Re-run history
What autonomous engineering needs
More than coding agents.
Impact-aware testing
Select the journeys affected by a code, configuration, model or prompt change.
Agentic exploration
Generate meaningful paths, edge cases and adversarial scenarios from system context.
Self-maintaining coverage
When a journey changes, detect the break and propose or apply the smallest safe repair.
Failure reproduction
Replay failures with traces, inputs and state so engineers can move from symptom to cause.
Production-to-regression
Turn real anomalies and user journeys into durable regression coverage.
Release intelligence
Connect test evidence to a release verdict instead of a dashboard full of disconnected green checks.
Agent assurance within the SDLC
Verify the agent's work and behaviour.
Goal completion
Multi-turn behaviour
Tool selection & arguments
RAG grounding
Guardrail enforcement
Model-version regression
Trajectory integrity
Security & adversarial behaviour
Start with one system
Connect one engineering workflow.
Start with one repository, one delivery workflow or one AI system. Map the lifecycle, identify where autonomous work needs verification, and connect the evidence required for a defensible release decision.
Map your Agentic SDLC