Is it risky to add AI to a working product?

Done carelessly, yes, which is why we integrate module by module with full test coverage and staged rollouts. Each AI feature is isolated, monitored, and reversible, so a problem in one module can never take down your product.

Which AI models do you work with?

We are model-agnostic and pick based on your needs: OpenAI and Anthropic for general intelligence, open models for data-sensitive or cost-sensitive workloads. If you have compliance requirements, we can run everything inside your own infrastructure.

How long does a typical integration take?

The audit and roadmap take two to three weeks. Individual AI modules typically ship in three to six weeks each, depending on complexity. Most clients have their first AI feature in production within two months of kickoff.

AI Codebase Integration

Already have a working product? You don't need a risky rewrite to benefit from AI. We audit your codebase, pinpoint the modules where AI creates the most value, and integrate them one by one, each module shipped, tested, and stable before we move to the next.

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Real-world problems

Sound familiar? Here's how we fix it.

The problem

Competitors ship AI features while you stand still

Your rivals just launched AI search, smart summaries, or an AI assistant inside their product. Your customers are starting to ask when you will have it. Every quarter you wait, the gap looks bigger and switching looks easier.

Our solution

We audit your codebase, find the highest-value insertion points, and integrate AI features module by module, search, summarization, copilots, classification. You ship AI capabilities in weeks, not after a year-long rebuild.

The problem

A full rewrite was quoted at six figures

An agency told you the only way to get AI is to rebuild the whole product. That means a year of disruption, a massive invoice, and the very real risk of breaking what already works and pays the bills.

Our solution

We integrate AI into your existing codebase without a rewrite. Each module is scoped, built, and tested in isolation against your current stack, so the product keeps running and every release is independently shippable and reversible.

The problem

Your team does not know where AI actually fits

Everyone agrees you need AI somewhere, but nobody can say where it creates real value versus gimmick. Random AI features get built, nobody uses them, and leadership concludes AI was hype.

Our solution

Our AI-readiness audit maps your product against proven AI patterns and scores each opportunity by user value and implementation effort. You get a ranked roadmap, what to build first, what to skip, before a single line of code is written.

The problem

A previous AI plugin broke things in production

Someone bolted an AI API onto the product and it hallucinated in front of customers, leaked prompt data, or fell over under load. Now the team is scared of AI and leadership has trust issues.

Our solution

We build with guardrails from the start: grounded responses from your data, output validation, rate limiting, and staged rollouts with monitoring. Every AI module ships with tests and rollback plans, so nothing reaches customers unproven.

Deliverables

What's included

AI-readiness codebase audit

Module-by-module integration roadmap

Incremental, tested AI rollouts

Docs & team handover

Proof, not promises

See it in action

AI Automation

Vertex SaaS: AI support ticket triage

Incoming tickets get classified, prioritized, and answered by AI in seconds, only the tricky ones reach a human agent, with full context attached.

Read the case study

Questions, answered

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Have an idea? Let’s ship it.

One conversation is all it takes to turn “someday” into a launch date. Free consultation, zero pressure, fixed quote.