AI Integration — Embed Intelligence into Existing Software
Add AI capabilities to the software you already use. No rewrite required. Works with your existing stack — whether it's Laravel, Spring, .NET, Django, Node.js, or a twenty-year-old legacy system.
Six ways to add AI to your stack
Choose the integration approach that best fits your architecture, team capabilities, and timeline.
Module
A ready-to-use module for your application. Import it, configure it, and start using AI features immediately. Works as a Composer package, Maven artifact, NuGet package, or npm module depending on your stack.
SDK
A language-specific SDK that encapsulates our AI capabilities in idiomatic classes, methods, and types. Full support for type safety, async, streaming, error handling, and built-in retry logic.
Package
A standalone package with its own dependencies, configuration, and lifecycle. Install it alongside your application without version conflicts. Supports offline mode and private deployments.
API
A RESTful or gRPC API that your application calls for AI inference, embedding, search, and generation. Language-agnostic, easy to test, works with any HTTP client. OpenAPI spec included.
MCP Server
A Model Context Protocol server that exposes your application's data and capabilities as tools for AI agents. Standardized interface, security boundaries, and interoperability with any MCP-compatible client.
Microservice
An autonomous AI microservice deployed alongside your application. Containerized, independently scalable, with its own health checks, monitoring, and deployment lifecycle. Docker/Kubernetes ready.
Works with your framework
Native integrations and battle-tested adapters for the most popular backend and frontend frameworks.
Backend Frameworks
PHP
Java / Kotlin
Node.js
Python
.NET
Other
Frontend Frameworks
Data & Infrastructure
Modernize without replacing
Your legacy system does not need to be rewritten to benefit from AI. We build adapters, bridges, and middleware that connect AI capabilities to older architectures.
Whether you are running PHP 5.6, Java EE, .NET Framework 4.x, COBOL backends, or decade-old monolithic systems — we can add AI capabilities as an additional layer.
API Gateway Pattern
Deploy an AI microservice that connects to your legacy system via existing APIs, database connections, or file exports. No modification to legacy code.
Database Bridge
Read directly from the existing database schema. AI capabilities are served from a read replica or cache layer, keeping the production system intact.
Webhook / Event Bridge
Your legacy system emits events; our AI layer listens and reacts. Incoming email triggers classification, form submission triggers validation, record change triggers analysis.
UI Overlay
Inject AI search, chat, or assistant widgets into your existing web UI via iframe, JavaScript snippet, or browser extension — without modifying application templates.
How AI integration works
A structured approach to adding AI capabilities to your existing software.
Analysis
Analysis of your stack, data flows, and AI opportunities.
Architecture
Design of the integration pattern and AI components.
Development
Development of modules, APIs, and adapters for your stack.
Testing
Integration testing, load testing, accuracy validation.
Deployment
Production rollout with monitoring and observability.
Evolution
Continuous improvement, new features, model updates.
Ready to add AI to your software?
Tell us about your stack. We will recommend the fastest integration path — no rewrite required.