AI Automation
We integrate custom LLM systems, LangChain agents, semantic search, and OpenAI processing pipelines.
Service Overview
The Operational Bottleneck
Repetitive customer support requests or unstructured document analysis slows down operations and overwhelms staff.
Our Engineered Solution
We integrate custom LLM systems, LangChain agents, semantic search, and OpenAI processing pipelines.
Business Outcome & Value
Instantly respond to support inquiries autonomously and extract structured insights from files in seconds.
Capabilities & Focus
- Semantic Search and RAG: Vector search over internal manuals, spreadsheets, and databases using Pinecone and PgVector for high-precision retrieval.
- AI Support Chatbots: Custom support agents using LangChain/LangGraph capable of securely verifying order status, processing support tickets, and scheduling consultations.
- Document Processing: Structured data extraction from invoices, contracts, receipts, and CVs using OCR and LLMs to automate background systems.
Tech Stack
Strategy Session
Let's discuss how to integrate these solutions to scale your business operations.
Book ConsultationService FAQ
How do you prevent AI models from hallucinating?
We implement Retrieval-Augmented Generation (RAG) structures using Pinecone semantic vector databases. By loading your company manual, files, or product inventories into the context window, the model references verified source files directly, keeping answers accurate and compliant.
Are the data and files shared with OpenAI kept private?
Yes. When calling models via the OpenAI Enterprise API or Azure OpenAI service, the data sent is explicitly not used for training public models. We also implement secure tokenization and PII redaction rules to ensure privacy compliance.
What AI models do you typically work with?
We work with OpenAI (GPT-4o, GPT-4), Anthropic Claude, Meta Llama, and deep learning frameworks like LangChain, LangGraph, and Llamaindex.