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Your platform still works. Your interface is losing users.

We rebuild the front-end experience of legacy SaaS products with a conversational AI layer. No core system rewrite. No downtime. Users get ChatGPT-style interactions on top of the platform they already use.

Trusted by product companies at every stage.

Siemens
Toyota
Rainbow Tours
PwC
Geberit
Chooose
Lexolve

Is your platform stuck in 2022?

  • Competitors already use AI.
  • Users leave for simpler products.
  • Rebuilding everything isn't an option.
  • Simple tasks take too many clicks.
  • New features get lost deep in the menus.
  • Our interface looks a decade old.
  • Competitors copy our features before we can react.
  • Sprints burn on UX debt, not new value.
  • New users need training.
  • Support keeps answering the same questions.
  • Customers ask when we'll add AI.
  • Nobody reads our product docs.

Your AI strategy doesn't need a better model. It needs a better integration layer.

78%

of enterprises can't connect AI tools to their existing systems.

Zapier Enterprise AI Survey, October 2025

60%

of AI leaders rank legacy integration as the #1 barrier to agentic AI, above skills and budget.

Deloitte Tech Trends 2026

288–362%

three-year ROI is what legacy modernization now delivers when integration is done right.

Kyndryl 2025 State of Mainframe Modernization Survey

A modern interface. On top of your existing system.

We add a conversational AI layer to your legacy platform. Users interact in plain language. Your core logic stays intact.

Users type or speak what they need. The AI interprets intent and returns the right action or answer.

What stays the same.

  • Your database
  • Your business logic
  • Your infrastructure
  • Your integrations

From legacy interface to AI-powered product in even 2 weeks.

  1. 01

    Discovery & Architecture Review

    We map your codebase, user flows, and the highest-friction areas. We identify which interactions are best candidates for conversational AI. You get a documented scope and interface specification.

    • Scope document
    • Interface specification
  2. 02

    AI Layer Design

    We design the conversational interface: interaction patterns, tone, role-based flows, and fallback handling. You review and approve before we build.

    • Interaction design
    • Stakeholder approval
  3. 03

    Integration

    We connect the AI layer to your existing system via API. We configure the language model on your codebase and content. No access to production data is required during this phase.

    • API integration
    • Model configuration
  4. 04

    Calibration

    We run accuracy and hallucination tests against real user scenarios. Edge cases are documented and handled. The assistant is calibrated to your user vocabulary and product terminology.

    • Accuracy report
    • Edge cases handled
  5. 05

    Launch & Monitoring

    We deploy to your environment. We provide 24/7 monitoring, access management, and ongoing optimization as your product evolves.

    • Deployed AI interface
    • Monitoring dashboard
    • Ongoing optimization

Results you can measure

Cut user onboarding time

Our client experienced a 95% time reduction — from 45 minutes to under 2.

Free up Customer Support

Reduce the volume of routine queries so your support team handles complex issues, not basic how-to questions.

Increase feature adoption

Make functionality discoverable through conversation. Users find what they need without training or documentation.

Give users new workflows natively

Users can create new workflows inside your product with native AI Tools, without switching to another tool.

Extend the life of your platform

Modernize the user experience without a full rebuild. Protect your existing investment.

Ship in weeks, not quarters

A modern user experience on top of your existing infrastructure, live in as little as two weeks.

Cybersecurity Management Platform | USA

Our client

Cybersecurity Management Platform | USA

The Challenge

Complex dashboards and static reports required expert-level training to interpret.

The Solution

We added a conversational AI layer to provide a context-aware chat interface grounded in the platform's live logic.

The Result

95% reduction in onboarding time, Self-serve data exploration, significant drop in support tickets, and users gained the ability to build new workflows natively. Core backend: unchanged.

Frequently asked questions

We work with your codebase to understand product logic, but we do not require production database access during the build phase. All AI responses are grounded in your documented logic and approved content. We handle access under NDA and follow your existing security protocols.

Yes. The conversational AI layer connects to your platform via API. We do not replace or modify your core system. We work with your existing tech stack and integrate with your SSO and access management.

A chatbot follows scripted decision trees. Our AI layer reads your actual codebase and product logic, understands user intent, and responds within the boundaries of what your platform does. It updates automatically as your product ships new features. It does not guess, and it does not generate answers from public AI training data.

Most implementations go live within 4 to 6 weeks. Timeline depends on codebase complexity, the number of user roles to configure, and the integrations required. We scope the timeline precisely in the discovery phase.

The AI layer stays in sync with your codebase. When you deploy changes, the assistant updates its knowledge base automatically. You do not need to manually maintain documentation for the AI to remain accurate.

InProduct AI is our product for SaaS companies that want to give their end customers a self-serve support experience. This service is for companies that want to modernize the core interface of their own platform. The underlying technology is related, but the scope and delivery model are different. We can advise which approach fits your situation in a 30-minute call.

We are ISO 27001 certified. We do not use your data to train AI models. All processing happens within your secure environment. Data is encrypted at rest and in transit. The assistant integrates with your existing SSO and access policies, so permission boundaries are preserved.

Your platform has more value than users are getting out of it.

Let's close the gap between what your product can do and what users actually experience.

A team trusted by product companies at every stage.

Siemens
PwC
Toyota