Engineering Service

AI Integration

Practical AI for production systems. LLMs, embeddings, RAG, and intelligent automation — no hype, just working AI features.

Capabilities

What we deliver

LLM Integration

OpenAI, Anthropic, and open-source model integration with proper prompt engineering.

RAG Pipelines

Retrieval-augmented generation with vector databases for domain-specific knowledge.

Embedding Pipelines

Document processing, chunking, and embedding for semantic search and retrieval.

Intelligent Automation

AI-powered workflows: classification, extraction, summarization, and decision support.

Use Cases

Where AI adds real value

Document Processing

Automated extraction, classification, and summarization of documents.

Semantic Search

Natural language search across your data using embedding-based retrieval.

Conversational AI

Domain-specific chatbots and assistants grounded in your data via RAG.

Decision Support

AI-augmented workflows for classification, scoring, and recommendation.

Approach

How we integrate AI

1

Define

Identify AI opportunities and define measurable success criteria.

2

Prototype

Rapid prototyping to validate approach and model selection.

3

Integrate

Production integration with error handling, fallbacks, and monitoring.

4

Optimize

Cost optimization, latency tuning, and accuracy improvements.

Technology

Tools we use

OpenAIAnthropicLangChainPythonFastAPIPostgreSQL (pgvector)Redis

Ready to add AI to your product?

We'll help you identify where AI adds real value, then build it.