We build autonomous AI infrastructure that eliminates manual back-office operations.
Designed for established companies that need precision engineering, not another wrapper.
What We Build
Autonomous Data Pipelines
We ingest raw unstructured data from emails, PDFs, and APIs, normalize it using multi-step LLM chains, and validate it against strict schemas before pushing to your database.
Python, LangChain, PostgreSQL
Intelligent Triage Systems
Not a chatbot. A routing engine that deeply analyzes support tickets, checks customer history, and drafts technical responses for human approval.
OpenAI API, Zendesk API, Vector DB
Document Extraction Engines
Parsing complex financial or legal documents with 99% accuracy by combining OCR with semantic understanding, handling edge cases that break traditional regex.
Azure Doc Intelligence, various LLMs
RAG & Knowledge Systems
Enterprise-grade Retrieval Augmented Generation (RAG) implementation. We build vector search architectures that allow your AI to securely access and verify your internal knowledge base.
Pinecone, Weaviate, LlamaIndex
Agentic AI Development
Building autonomous agents that can plan, execute, and self-correct complex workflows. Multi-agent systems that coordinate to solve high-level business goals.
LangGraph, AutoGen, CrewAI
Enterprise LLM Solutions
Secure deployment of private LLMs and fine-tuning services. We integrate powerful AI capabilities into your existing stack while maintaining data privacy and security.
vLLM, Ollama, HuggingFace
How We Work
Discovery
We audit your manual workflows to find what can actually be automated. If AI isn't the right tool, we tell you immediately.
Build
We develop the core logic locally, testing edge cases. We don't just prompt-engineer; we write robust code around the models.
Delivery
We deploy to your infrastructure or ours. Handover includes full documentation, environment setup, and code walkthroughs.
Support
We provide 30 days of monitoring to catch edge cases. After that, we offer maintenance retainers, but we prefer to empower your team to own the system.
Examples
Logistics Routing Engine
The Problem: A logistics firm was manually matching hundreds of shipments to carriers daily, wasting 20+ hours.
The Reality: Off-the-shelf logistics software was too rigid. They needed custom logic for specific cargo types and carrier preferences.
The Solution: We built a decision engine that parses shipment manifests and queries carrier APIs. It doesn't "guess" — it rules out invalid carriers deterministically, then uses an LLM only for parsing fuzzy unstructured notes.
Code: Fine-tuned extraction model + rigid rules engine in Python.
Financial Report Analyzer
The Problem: Analysts were spending weeks converting PDF tables into Excel models.
The Constraints: 100% accuracy required. Hallucinations were unacceptable.
The Solution: We implemented a "Human-in-the-loop" pipeline. The system extracts data with confidence scores. High confidence goes straight to DB; low confidence is flagged for human review. This reduced manual work by 90% while maintaining accuracy.
Who This Is Not For
We are careful about who we work with.
Mutual fit is critical for complex engineering.
If you want "Magic"AI is probabilistic software, not magic. It requires testing, iteration, and occasional maintenance. If you expect zero error rates immediately without human oversight, we are not a fit.
If you need it yesterdayGood engineering takes time. We don't rush security or stability for a demo.
If you're looking for a cheap wrapperWe build custom infrastructure. We are more expensive than a $20/month SaaS tool, but we solve problems those tools can't touch.
Start the Conversation
Ready to engineer a solution?
Send us a brief email describing the manual workflow you want to replace. We don't need a full spec, just the problem.
We will reply within 24 hours to tell you if it's feasible and if we are the right team.