Agentic Delivery Assurance Platform

AI-first delivery needs an assurance layer.

Defynra coordinates agents, security, compliance, and delivery evidence from requirement to runtime—so your teams can move at AI speed without turning software delivery into a black box.

Assess your AI delivery readiness Follow one change

Autonomy earned by verification Consequential decisions stay human Aggregate metrics, never developer surveillance

CHANGE PASSPORT · ILLUSTRATIVE CHG-2047

SUPERVISED

Approved intent Add step-up verification to payout approval JIRA-814 · AC-01…05 · ADR-027

01
Requirement tracedAcceptance criteria and policy boundary loaded
spec✓
02
Plan constrainedArchitecture decision and permitted files declared
plan✓
03
Change preparedCode, tests, and draft merge request produced
mr!247
04
Evidence verifiedTests, scans, provenance, and skipped checks recorded
9/9✓
05
Human decision requiredNamed reviewer owns approval and merge
WAIT
06
Runtime closes the loopDeployment, posture, and DORA impact join the record
next

Every important change has a reason, a record, and a reviewer.sha256:8c71…a04e

BUILD WITH AGENTS GOVERN WITH EVIDENCE MEASURE THE OUTCOME

The AI delivery tension

Generation got faster.
Assurance became the bottleneck.

AI compresses the time to produce software. The pressure moves downstream—to requirements, architecture, verification, security review, release confidence, evidence collection, and operational learning.

WHEN AI IS ISOLATED IN THE EDITOR

More changes arrive than reviewers can confidently absorb.
Tests and security checks become claims instead of evidence.
Exceptions, approvals, and release context scatter across tools.
Leaders cannot tell whether AI improved delivery or moved risk downstream.

WHEN AI WORKS INSIDE A DELIVERY SYSTEM

Each agent has a role, skills, permissions, and evidence obligations.
Autonomy matches verification strength, risk, policy, and production impact.
Every handoff preserves intent, artifacts, decisions, and source records.
DORA and security outcomes show whether the stronger system works.

The Defynra answer

One operating model from intent to runtime.

Defynra connects the work of people and agents to a governed delivery system. It does not replace your systems of record; it makes the path between them explicit, controlled, and measurable.

Agentic delivery, end to end

Specialists collaborate across requirements, architecture, implementation, quality, security, release, operations, and governance.

Autonomy earned by evidence

Execution mode is selected per change—not enabled as a platform-wide leap of faith.

Security in the flow

Coverage, findings, supply-chain integrity, runtime posture, exceptions, and approval evidence travel with the change.

DORA with source records

Definitions, distributions, windows, deployments, incidents, and approvals remain attached to every measure.

Human accountability

Agents prepare, explain, verify, and recommend. Authorized humans own consequential decisions.

The Agentic Delivery Fabric

A software company’s delivery roles—coordinated, not collapsed.

Each assistant works from governed knowledge and permitted operations. Collaboration preserves professional boundaries instead of pretending one general-purpose agent can own every decision.

BABusiness Analystintent · requirements · traceability

SASolution Architectdesign · boundaries · change review

BIBinaagoverned implementation engine

QEQuality Engineertest evidence · release readiness

SCSecurity Championfindings · exposure · exceptions

DODevOpspipeline · deployment · operations

GVGovernancepolicy · approvals · accountability

Product direction: the roster represents the governed operating model. Availability is released assistant by assistant; demonstrations and planned capabilities are labelled as such.

Binaa · implementation engine

Not “AI writes code.” A reviewable change with a proof package.

Binaa turns an approved story into a bounded implementation. It researches the governed references, proposes an approach, plans the change, executes in the designated workspace, and reviews the result before preparing a draft merge request.

RResearch IInnovate PPlan EExecute RReview

Demonstration workflow: approval and merge remain with the designated human role. Supported targets and verification depth are confirmed during a pilot.

VERIFICATION ENVELOPE · DRAFT MR !247B

Specification: JIRA-814 · AC 5/5
Change boundary: 7 files · 214 + / 38 −
Tests present: xUnit · Playwright
Security evidence: SAST · SCA · secrets · image
Skipped checks: none hidden
Required decision: human review + merge

commit 97af21cproof 8c71a04e

The Evidence Spine

From intent to runtime, one evidence chain.

Every major claim should lead somewhere real: a requirement, definition, policy, test, finding, approval, deployment, or runtime record. Missing, stale, restricted, and not-evidenced states stay visible.

intentrequirementdesigncodetestssecurityreviewreleaseruntime

ILLUSTRATIVE DORA RECORD

26h · p85

Lead time for changes

commit accepted → production promotion · p50 / p85 / p95 · trailing 30 days

reviewqueuepipelinepromotion

deployment → MR → commit → approval

DORA explains movement

Deployment frequency, lead time, change failure, recovery, and flow retain their definitions, windows, distributions, and source records.

Security explains what moved

Coverage first, then findings, exploitability, remediation, risk acceptance, and exposure.

Runtime explains what is real

SBOM, provenance, admission policy, workload posture, and behavioral evidence connect code to what is running.

Absence is a first-class state

A scanner that did not run is not a clean result. Defynra says not evidenced—never zero.

Autonomy and accountability

Autonomy is a decision per change—not a switch.

Defynra considers code longevity, verification strength, risk, policy, and production impact. Higher autonomy must be earned by stronger evidence and narrower consequences.

Supervised

The agent researches, proposes, and prepares. A human directs execution step by step.

Best for unfamiliar, high-impact, or weakly verified work.

Confirmation-based

The agent executes bounded work but pauses before consequential operations.

Best when checks are strong and decisions still carry material impact.

Autonomous

Only bounded, policy-permitted work with strong independent verification qualifies.

Never a shortcut around architecture, risk acceptance, release, or production authority.

Agents prepare, explain, verify, and recommend.Humans own requirements, architecture, risk acceptance, release approval, and production decisions.

Why Defynra

The centre is the delivery outcome—not the tool category.

Familiar categoryDefynra expands the centre

Coding copilots → code generationGoverned delivery outcomes: intent, tests, security, review, release, and runtime.

Security tools → findingsCoverage, deployment context, exposure, decisions, expiry, and verified remediation.

Engineering intelligence → trendsEvidence-backed measures connected to security, governance, and source records.

Traditional GRC → periodic collectionControls and accountable decisions embedded in delivery as it happens.

No individual productivity surveillance. No composite “engineering health” score. No claim of compliance without formal evidence.

AI-first delivery readiness assessment

Find where AI speed is outrunning your delivery system.

Map where agents operate today, how changes are verified, which decisions remain accountable, and whether delivery and security outcomes can be traced to evidence.

Agent use across requirements, code, tests, security, and release
Autonomy and human-decision boundaries
Verification, supply-chain, runtime, and DORA evidence gaps
A practical pilot path around your systems of record