What Changes

Four Outcomes That
Change the Economics.

⚡

Compressed Cycles

Requirements in hours, not weeks. Architecture decisions documented before debates drag on. Sprint planning that reflects reality. The entire delivery heartbeat accelerates.

🔬

Quality Upstream

Defects caught at requirements, not in production. Tests written before code. Security embedded from line one. Agents move quality upstream — where fixing problems is fast, cheap, and consequence-free.

📊

Predictable Delivery

When agents structure every phase, the unknowns shrink. Estimates tighten. Overruns become the exception. Delivery becomes something you can actually forecast.

🔭

Full Observability

Every agent action logged. Every decision traceable. Governance, audit trail, and compliance built into the delivery model — not retrofitted when regulators ask.

The Agent Ecosystem

Nine Agents.
One Pipeline. Zero Gaps.

Select any agent to explore what it owns, what it delivers, and what changes when it's in the loop.

How It Works

From Brief to
Production in Four Moves.

1📋

Understood

ClariX structures requirements. Gaps and contradictions surfaced before a single line of code is written.

2🏗️

Designed

StratiX generates architecture options with trade-offs. TrackX turns the chosen direction into an executable sprint plan.

3⚙️

Built

CraftX and ForgeX generate frontend and backend code. VaultX handles the data layer. GuardX scans for security across every commit.

4🚀

Shipped & Supported

VeriX validates before release. FleetX manages deployment and monitors production — predicting incidents before users notice them.

Prompt Library

Production-Ready Prompts
for Every Phase.

Effective agentic delivery depends on well-engineered prompts. Our library gives your teams a tested starting point.

Governance & Quality

Agentic AI You Can
Trust, Audit & Control.

Deploying AI agents in a production delivery environment demands structured governance — evaluations, drift detection, testing frameworks, and clear audit trails at every phase.

📊

Evaluation Framework

Every agent output evaluated against structured criteria — correctness, completeness, consistency, and project alignment.

Output accuracyContext fidelityFormat adherenceRegression checks

📡

Drift Detection

Agent behaviour drifts when models update or context shifts. Continuous monitoring against baselines catches performance changes before they affect delivery.

Baseline monitoringThreshold alertsAuto re-calibration

🧪

Agent Testing

Agents tested like software — defined test cases, expected outputs, regression suites. No prompt or model change reaches production without validation.

Regression suitesEdge case coverageAdversarial testing

📋

Audit & Compliance

Every agent decision traceable end-to-end. Exportable audit reports, role-based access controls, and data residency compliance built in.

Decision traceabilityExportable reportsRBAC

🔄

Versioning

Every prompt, model version, and configuration change tracked. Full rollback capability if a version introduces regressions.

Prompt versioningConfig trackingInstant rollback

👤

Human-in-the-Loop

Every significant output has a structured review touchpoint. Escalation paths are explicit — agents know when to hand off to a human.

Confidence thresholdsReview gatesOverride logging

Agent

Produces output

→

Eval

Scored & checked

→

Human

Reviews if needed

→

Deliver

Approved output

Agent Impact

Metrics That Matter
for Each Phase.

Each agent operates in a different phase with different success criteria. These are the metrics that matter most — specific to each role.

↓ 58%

Average reduction in overall delivery cycle time

↓ 65%

Defects reaching production across all engagements

↑ 3.2×

Engineering team output per sprint with agents active

↑ 91%

On-time delivery rate vs. 34% industry average

🤝 Development Partnership · Live in Production

We Didn't Just
Design This.
We're Building It.

MySavi.ai is a greenfield product — built from a blank page with a GenAI-first architecture from day one. Predikly is not a vendor. We are the development partner, embedded from the first line of code.

"This isn't a case study written after the fact. It's a partnership we're inside — building, learning, and proving the model in production as we go."

Read the Partnership Story

GenAI

Architecture from first principles — not retrofitted onto existing patterns

9

Agentic roles active across the full development lifecycle

0→1

Greenfield product, blank page to production environment

Live

Active partnership — not a historical case study

⚡ Enhancement Acceleration · Active Engagement

Accelerating Delivery on
Codebases That
Already Exist.

Not every engagement starts from a blank page. We work with enterprise clients carrying significant existing codebases — using Claude Code, OpenAI Codex, Gemini Code Assist, and our agent ecosystem to understand the code deeply, identify enhancement opportunities, and compress delivery cycles on platforms that have been in production for years.

"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."

Learn About Enhancement Acceleration →

↑ 2×

Enhancement delivery speed on existing codebases

↓ 60%

Time to understand and document legacy architecture

Active

Live engagement — agents embedded in client delivery team

Claude Code

Plus OpenAI Codex and Gemini Code Assist — AI-powered codebase analysis, enhancement, and support

For Your Leadership Team

What This Means
in the Room That Matters

For the CIO / COO

Deploying AI agents inside enterprise delivery raises legitimate governance questions — and we've built for exactly that scrutiny. Every agent action is logged with full input-output 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

Engineering overruns aren't a people problem — they're a visibility problem. When requirements are ambiguous, estimates are optimistic, and defects surface late, every project drifts. Agents enforce structure at every phase — validated requirements, tracked dependencies, quality gates that catch problems early. Your project forecasts start reflecting reality rather than hope.

For the CTO

Your senior engineers are solving the wrong problems. Not because they lack judgment — because they're buried in scaffolding, boilerplate, and process overhead that consumes the hours where real architectural thinking should happen. Agents take ownership of the systematic work. Your technical leaders get back to the decisions that actually determine whether the product holds up under pressure.

For the CPO

The six-month spec cycle is a bet — and most product leaders know it. By the time engineering delivers, the assumptions behind the spec have already shifted. When build cycles compress from quarters to weeks, you stop placing large bets on static requirements and start running smaller, faster experiments against real user behaviour. The economics of being wrong change fundamentally.

How We Engage

Three Ways to Start.

Greenfield

01

Build Something New

A product idea, a platform, or a system that doesn't exist yet. We build it with agentic AI embedded from the first line — the way MySavi.ai is being built right now.

Legacy

02

Evolve What Exists

You have a codebase with years of history and no documentation. We use Claude Code, OpenAI Codex, Gemini Code Assist, and our agent ecosystem to understand it deeply, surface opportunities, and accelerate delivery.

Augmentation

03

Extend Your Team

Need agentic capability inside your current team? We embed alongside your engineers — bringing our framework into your workflow and leaving you with a genuinely different capability.

Ship Software
at a Different
Velocity.

Four Outcomes That
Change the Economics.

Nine Agents.
One Pipeline. Zero Gaps.

From Brief to
Production in Four Moves.

Production-Ready Prompts
for Every Phase.

Agentic AI You Can
Trust, Audit & Control.

Metrics That Matter
for Each Phase.

We Didn't Just
Design This.
We're Building It.

Accelerating Delivery on
Codebases That
Already Exist.

What This Means
in the Room That Matters

Three Ways to Start.

See It Applied to
a Real Challenge.

Ship Softwareat a DifferentVelocity.

Four Outcomes ThatChange the Economics.

Nine Agents.One Pipeline. Zero Gaps.

From Brief toProduction in Four Moves.

Production-Ready Promptsfor Every Phase.

Agentic AI You CanTrust, Audit & Control.

Metrics That Matterfor Each Phase.

We Didn't JustDesign This.We're Building It.

Accelerating Delivery onCodebases ThatAlready Exist.

What This Meansin the Room That Matters

Three Ways to Start.

See It Applied toa Real Challenge.

Ship Software
at a Different
Velocity.

Four Outcomes That
Change the Economics.

Nine Agents.
One Pipeline. Zero Gaps.

From Brief to
Production in Four Moves.

Production-Ready Prompts
for Every Phase.

Agentic AI You Can
Trust, Audit & Control.

Metrics That Matter
for Each Phase.

We Didn't Just
Design This.
We're Building It.

Accelerating Delivery on
Codebases That
Already Exist.

What This Means
in the Room That Matters

See It Applied to
a Real Challenge.