AI Integration
AI that works in production — not just in demos.
We integrate large language models, RAG pipelines, and AI-powered features into production applications. From customer support chatbots that resolve 73% of tickets on average to document processing systems that save hours per day — we build AI features with guardrails, fallbacks, and cost management built in from day one.
Ask it the wrong thing.
A good AI feature knows what it knows. Try one it can answer, one it can’t, and one meant to trick it.
Capabilities
What we deliver.
- 01
RAG Pipelines
Retrieval-augmented generation with vector databases for accurate, grounded AI responses.
- 02
Chatbots & Copilots
Customer support bots, internal copilots, and conversational interfaces powered by LLMs.
- 03
Document Processing
Automated extraction, classification, and summarization of documents at scale.
- 04
Guardrails & Safety
Input validation, output filtering, hallucination prevention, and content safety controls.
- 05
Model Selection
Intelligent routing between premium and smaller models from OpenAI and Anthropic to optimize cost and quality.
- 06
Evaluation & Monitoring
Automated accuracy testing, cost tracking, and continuous performance measurement.
Technology
The stack.
- OpenAILLM
- AnthropicLLM
- LangChainOrchestration
- PineconeVector DB
- Vercel AI SDKFramework
- pgvectorVector DB
Process
How we work.
- 01
Assessment
Use case validation, data inventory, and feasibility analysis.
- 02
Pipeline
Data ingestion, embedding, retrieval architecture, and prompt engineering.
- 03
Integration
API development, UI components, streaming responses, and error handling.
- 04
Production
Guardrails, cost management, evaluation suite, and monitoring dashboards.
Use Cases
Who this is for.
- Customer support chatbots with company-specific knowledge
- Internal search over documentation and knowledge bases
- Automated document review and data extraction
- Content generation tools with brand voice guardrails
- Recommendation engines powered by semantic search
From the Blog
Deep dives on this topic.
FAQ
Common questions.
Which AI models do you work with?
We work with OpenAI, Anthropic, and open-source models. We use intelligent model routing to optimize cost and quality — simple queries go to cheaper models, complex ones go to premium models.
How do you prevent AI hallucinations?
Through RAG (Retrieval-Augmented Generation) architecture. Instead of relying on the model's training data, we retrieve relevant context from your actual business data and instruct the model to answer only from that context.
What does AI integration cost to run monthly?
For a SaaS product with 10,000 active users, typical monthly AI infrastructure costs range from $100-500 depending on usage volume and model mix. Intelligent routing reduces costs by 60-75%.
Can you build a chatbot for our website?
Yes. We build customer support chatbots that learn from your documentation, FAQ, and knowledge base. Implementations resolve 60-75% of support tickets without human intervention, with an average of 73%.
Let's build.
Tell us about your project. We respond within 24 hours with clear next steps.
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