Codebases That
Already Exist.
Delivery That Doesn't
Have to Slow Down.

Your platform has a decade of history, undocumented decisions, and a backlog that grows faster than your team can ship. We use frontier AI coding models and our nine-agent ecosystem to understand the code deeply, then compress delivery cycles on systems already in production.

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The Reality

Most Enterprise Software
Wasn't Built Yesterday.

The challenge isn't building new things. It's making the things you already have work better, faster, and more reliably — without breaking what's already serving customers.

🏚️
Nobody Fully Understands the Architecture
The original architects left years ago. Documentation is incomplete or outdated. Every enhancement starts with weeks of archaeology just to understand what already exists and why.
📈
The Backlog Grows Faster Than You Ship
Enhancement requests pile up because every change requires understanding cascading dependencies. Senior engineers spend 60% of their time reading code rather than writing it.
⚠️
Rewriting Isn't an Option
The system is load-bearing. It serves customers every day. It needs to keep running while it gets better. You need acceleration, not replacement — and the delivery model needs to respect that reality.
The Approach

Three Capabilities.
One Acceleration Model.

We don't start by writing code. We start by understanding what already exists — then compress every phase of enhancement delivery.

🔍
Legacy Code Analysis
AI-powered architecture mapping that turns months of archaeology into days. We map dependencies, surface undocumented decisions, and build a complete understanding of your codebase before any enhancement work begins.
↓ 60%
Time to understand
legacy architecture
Days
Not months for
full codebase mapping
Enhancement Acceleration
Agents and frontier coding models working within your existing codebase to compress delivery cycles. Enhancements, features, and fixes that used to take sprints now take days — with full regression coverage built in.
↑ 2.5×
Enhancement
delivery speed
↑ 85%
On-time delivery
for enhancement sprints
🛟
Intelligent Support
AI-powered triage that uses actual codebase context to diagnose issues — not just pattern-matching on symptoms. L1/L2 support moves from guesswork to informed resolution, with full architectural awareness behind every diagnosis.
↓ 45%
Mean time to
resolution
Context
Codebase-aware
triage from day one
The Instruments

Frontier Coding Models.
Applied to Legacy Systems.

These aren't autocomplete assistants. They're the instruments that make deep codebase analysis and rapid enhancement possible at enterprise scale.

Claude Code
Deep architectural understanding of large codebases. Maps dependencies, identifies patterns, surfaces undocumented behaviour. The primary instrument for legacy code analysis — turning tribal knowledge into documented architecture.
Architecture mappingDependency analysisCode comprehension
OpenAI Codex
Rapid code generation and transformation within existing patterns. Accelerates enhancement work by generating code that's consistent with your codebase's conventions — not generic boilerplate that needs to be rewritten.
Code generationPattern matchingRefactoring
Gemini Code Assist
Cross-file reasoning and large context window analysis. Particularly effective for understanding how changes in one part of a legacy system cascade through interconnected modules and services.
Cross-file analysisImpact assessmentLarge context
The Agent Ecosystem

Nine Agents. Reframed
for Enhancement Work.

The same nine-agent ecosystem that powers our greenfield development — reconfigured for the realities of existing codebases. Every agent's wording, capabilities, and metrics are tuned for enhancement, not blank-page builds.

Phase 1 — Understand & Plan
📋
ClariX
Requirements Analyst
🏗️
StratiX
Architecture Assessor
🧭
TrackX
Enhancement Planner
Phase 2 — Enhance
🎨
CraftX
Frontend Enhancement
⚙️
ForgeX
Backend Enhancement
🗄️
VaultX
Schema Migration
Phase 3 — Deliver & Govern
🛡️
VeriX
Regression Testing
🚀
FleetX
Safe Deployment
🔒
GuardX
Production Governance
↑ 2.5×
Enhancement delivery speed
on existing codebases
↓ 60%
Time to understand and
document legacy architecture
↓ 45%
Regression defects on
enhancement releases
↑ 85%
On-time delivery rate
for enhancement sprints

Metrics measured across active enhancement engagements. Individual outcomes depend on codebase maturity, team size, and system complexity.

The Economics

Before and After.
On Systems Already in Production.

Where the time and cost actually go in enhancement work — and what changes when agents and frontier models are embedded in your delivery team.

Codebase Understanding
Before
Weeks of archaeology. Senior engineers reading code to reconstruct undocumented architecture. Tribal knowledge locked in people who may have left.
With Predikly
Days, not months. AI-mapped architecture with documented dependencies, decision rationale surfaced, and full system understanding before any enhancement begins.
Enhancement Planning
Before
Every enhancement estimated with uncertainty. Impact analysis is guesswork. Dependencies discovered mid-sprint, forcing re-planning.
With Predikly
Dependency-aware planning with accurate impact assessment. Agents surface cascading effects before work begins, not after it's already underway.
Build & Regression
Before
Changes break unexpected things. Regression testing is manual and incomplete. Every release is a calculated risk against the existing system.
With Predikly
Full regression coverage generated alongside every enhancement. Agents verify changes against the existing system's behaviour, not just the new feature's requirements.
Deployment
Before
Manual deployment processes. Rollback plans that haven't been tested. Downtime windows negotiated weeks in advance.
With Predikly
Zero-downtime deployments with automated rollback. FleetX manages the release process with full observability and instant recovery capability.
Enterprise Governance

Agents on Production Systems
Demand Higher Scrutiny.

When agents are making changes to systems already serving customers, governance isn't optional — it's the foundation. Every control is built in from day one, not retrofitted when regulators ask.

🎯
Decision Boundaries
Agents operate within defined authority limits on existing systems. No changes to production architecture without human approval. Confidence thresholds and explicit escalation triggers for every operation.
Authority limitsEscalation triggersConfidence thresholds
📊
Quality Monitoring
Continuous monitoring against existing system baselines. Performance changes caught before they affect production. Drift detection ensures enhancements don't degrade what's already working.
Baseline monitoringThreshold alertsDrift detection
🧪
Agent Testing
Agents tested against the existing codebase's actual behaviour — not just generic test cases. No prompt or model change reaches production without validation against your specific system.
Regression suitesEdge case coverageAdversarial testing
📋
Audit & Compliance
Every agent decision on every enhancement traceable end-to-end. Critical for regulated industries where changes to production systems need complete audit trails.
Decision traceabilityExportable reportsRBAC
🔄
Versioning & Rollback
Every prompt, model version, and configuration change tracked. Full rollback capability — essential when agents are making changes to systems already serving customers.
Prompt versioningConfig trackingInstant rollback
👤
Human-in-the-Loop
Every significant output has a structured review touchpoint. On legacy systems where the risk of unexpected side effects is higher, agents know when to hand off — and provide full context when they do.
Review gatesContext handoffOverride controls
Proof Point

Already in Production.
Not a Concept.

"The codebase had a decade of history and no documentation. Within weeks, the team had full architectural visibility and was shipping enhancements at twice the previous pace."
↑ 2.5×
Enhancement delivery speed
↓ 60%
Time to map architecture
100K
Lines of code — impact analysed in 8 hours
Active
Live engagement — not historical
For Your Leadership Team

What This Means
in the Room That Matters

For the CIO / COO
Governance on production systems — built in, not bolted on.
Every agent action on your existing codebase is logged with full traceability. Decision boundaries are explicit. Escalation paths are defined. Your risk and compliance teams won't need to retrofit controls — they're already in the architecture.
For the CFO
Enhancement costs become predictable, not archaeological.
When every enhancement doesn't start with weeks of investigation, your forecasts start reflecting reality. Agents compress the understanding phase that makes legacy work so unpredictable. Budget overruns shrink because uncertainty shrinks.
For the CTO
Your senior engineers stop doing archaeology and start doing engineering.
The best technical minds in your organisation are spending 60% of their time reading legacy code instead of designing solutions. Agents handle the systematic understanding. Your architects and senior engineers get back to the decisions that actually require human judgment.
For the CPO
Faster enhancement cycles mean faster iteration on what customers need.
When the backlog isn't bottlenecked by legacy complexity, product teams can iterate on customer-facing improvements at the speed the market demands. Enhancement requests stop being multi-sprint projects and start being responsive delivery.
Ready When You Are

Let's Have a Straight Conversation

Not a pitch. Not a scripted demo. A direct conversation about where your software delivery or process automation sits today — and whether Predikly is the right partner to close the gap.

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We speak with CTOs, CPOs, CIOs, and COOs directly. No intermediary layer. No pitch deck in the first meeting.