Agentic Development Life Cycle

AI agents already write your code. Now let them run the whole lifecycle.

Not just coding. Discovery, specs, impact, delivery and audit, every phase runs on agents with full context of your system. POLYREQ is the ground truth they draw from.

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Methodology proven in:
Banking
Insurance
Automotive
Telco
Why SDLC is not enough

AI made development fast.
SDLC is breaking underneath it.

Your agent answers differently today than next week

The same question, two different impact analyses. They can only be saved as prose, impossible to compare, repeat, or defend in front of an auditor.

Approvals hang on text that keeps getting rewritten

After an agent rewrites the documentation, the approved use case gets renamed, merged or disappears. Nobody can say what exactly was approved, or whether it still holds.

An analysis sounds complete even at half coverage

An agent’s output shows only what it contains. There is no inventory of the system to check what it left out. “Nothing else changes” is a belief, not a fact.

Collisions and deviations surface when it’s too late

Two in-flight changes to the same part of the system meet in production. And comparing the approved state with what’s deployed is a manual project, every time.

The lifecycle, agentic

Seven phases. Agents in every one.

Not a specification tool. The platform the whole Agentic Development Life Cycle runs on, from business need to production.

The SDLCWaterfall, Agile or DevOps · disconnected tools, context lost between phases
ADLCthe same lifecycle · now run by AI agents

Business discovery

Business talks through its requirements with AI agents, plainly.

Impact + prototype

Every affected part is mapped, then shown in a clickable prototype.

v3

Technical specification

The validated change is written up as versioned technical specs.

Agentic
delivery

Coding agents build the software via MCP, with humans approving.

Automated verification

Each build is checked against the approved spec, automatically.

Controlled
release

Shipped to production, with approved-vs-deployed confirmed.

Traceability & audit

A full trail from idea to production, auditable at any time.

One living specs graph the shared context every phase reads and writes
The engine under ADLC

One living model of your system. From business rule to database table.

Every phase of ADLC runs on the same foundation: a living knowledge graph of records. Use case, rule, screen, endpoint, table, everything with identity, versions and links backed by evidence in code, built by AI, governed by people. Know-how from large-scale enterprise projects in insurance, banking, and automotive.

Specifications as versioned records

Your analysts feed in business requirements in any format. POLYREQ generates a structured, cross-referenced specification in hours, and every artifact gets its own ID, history and links that survive even AI rewrites.

A complete impact map for every change

A change is evaluated against the whole model: every part of the system affected with evidence in code, or untouched with a reason. The map is a stored artifact, repeatable, comparable, with collisions between two changes visible instantly.

Precise context for people and AI agents

Business changes the clickable prototype with a prompt and the specification updates in the background. Coding agents pull exactly the context they need via MCP. Precise input, precise output.

Agents + POLYREQ

Agents without POLYREQ vs. with POLYREQ

The difference is not what the AI writes. It is what you can repeat, check, and defend afterwards.

Agents without POLYREQ Agents with POLYREQ
The approved record
Documentation is prose. After an agent rewrites it, the approved use case gets renamed, merged or disappears, and the approval hangs on a paragraph that no longer exists.
Every artifact has identity, versions and links. Approval is attached to a record, not to a paragraph of text. A year later you can still say: we approved UC-012 v3, in this exact wording.
Impact analysis
One answer today, a slightly different one next week. You can save it, but as prose that is hard to search and impossible to compare.
A stored, repeatable artifact. You can show exactly what the analysis said on the day it was approved, even to an auditor.
System coverage
An agent’s analysis shows only what it contains. There is no inventory of the system to check it against, so it sounds complete even at half coverage.
Every part of the system is evaluated: affected with evidence in code, or untouched with a reason. “Nothing else changes” can be verified even by someone who has never read the code.
Change collisions
A conflict between two in-flight changes is found ad hoc, or only once the work is done.
Overlapping impact maps reveal the collision at analysis time. Two analysts find out about each other before they build the same thing differently.
Approved vs. deployed
Comparing the approved state with what is deployed is a manual project, every single time.
Runs automatically over linked records. Every difference is a tracked finding with an owner, it cannot vanish as a silent deviation.

And your agents? Via MCP they read the records and links straight from POLYREQ. We make them better, not obsolete.

See it live →
What you get

Results for your team. Not just technology.

Diamond

Approvals that survive every rewrite

You approve a record, not a paragraph of text. A year later you can still say: we approved UC-012 v3, in this exact wording, with these impacts, no matter how many times AI rewrote the documentation in between.

Microscope

Scenario analysis

What if the payment gateway goes down? What if traffic spikes 10×? POLYREQ identifies these scenarios in the specification, not when they surface in production.

Lego

Requirement changes? Impact with evidence.

The platform shows the impact on screens, rules, tests and code, with evidence, not estimates. And two analysts see the collision between their changes at analysis time.

Checkmark

Scope quantification

Every use case is quantified using Function Point Analysis (ISO/IEC 20926). You know exactly how much each part of the system costs and how much a change costs.

Chain

Audit trail from requirement to code

At any point you can see why something exists in the system, who requested it, and where it lives in the code. Every difference between approved and deployed is a tracked finding with an owner.

Globe

Industry-proven methodologies

The platform is built on TOGAF, BABOK, UML, ITIL, and ISO standards. Not because it sounds impressive, because it delivers results.

Comparison

From requirements management to a system of record over your code.

Traditional tools manage manually created requirements. POLYREQ builds and maintains a linked model from business to code, and computes impacts, collisions and deviations from it.

Capability Traditional requirements tools POLYREQ
Requirements management Yes Yes
AI specification generation from business input No Yes
Record identity & versions that survive AI rewrites Manual records only Automatic
Complete impact map computed from code No Yes, repeatable
Collisions between in-flight changes No At analysis time
Approved vs. deployed comparison Manual project Automatic
Clickable app-preview from requirements No Yes
Context for coding agents (MCP) No Yes
Scope quantification (Function Points) No ISO/IEC 20926
Why enterprises choose us

Proven methodology. Secure platform. Partner program.

Enterprise DNA

Methodology forged in banking, insurance, automotive, and telecom, across decades of enterprise delivery.

Security & Compliance

Designed from the ground up for regulated industries.

  • GDPR Compliant
  • Zero AI Data Retention
  • Isolated AI Context
  • Human-in-the-Loop

Design Partner Program

Now onboarding enterprise design partners. Early partners get:

  • Priority platform access
  • Dedicated onboarding & support
  • Direct roadmap influence
  • Limited spots available
Let's talk about your project →

Looking for custom development from specification to delivery?

See our E2E development →

Same question. Same answer. Every time.

The same change request twice through your agent: two different answers. Twice through POLYREQ: the same map, with every part of the system evaluated. Book a demo, we’ll show you live, on your own use cases.

Schedule a Demo

Or contact us directly: contact@polyreq.com

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