Home / Services / AI Development
Build products that think, learn and act.
We design and develop AI-powered products, intelligent workflows and automation systems that turn data and business processes into real-world outcomes.
We don't just integrate AI APIs. We build AI-powered products and workflows around real business problems.
Capabilities
What we build, and when it's the right call.
Generative AI
Drafting, summarising, extracting and transforming content inside a product, with guardrails and a review step where the output matters.
High-volume text work
AI Agents
Multi-step workflows where the model plans, calls your systems and reports back. Built with LangGraph so each step is observable and can be replayed.
Multi-step processes
RAG systems
Answers grounded in your own documents, contracts and tickets, with citations back to the source so people can verify what they read.
Private knowledge
LLM applications
Product features with a model behind them - search, classification, routing, enrichment - designed around latency and cost per call.
In-product intelligence
AI chatbots
Support and internal assistants that escalate cleanly instead of guessing, wired to your ticketing and CRM.
Support load
NLP
Classification, entity extraction, sentiment and language pipelines over messy real-world text.
Structuring text
Machine learning
Classical models where they beat an LLM on cost and reliability - churn, scoring, demand, anomaly detection.
Data-rich, narrow tasks
Computer vision
Inspection, counting, presence detection and OCR with OpenCV and TensorFlow, on server or on device.
Cameras & inspection
Predictive AI
Forecasting demand, load, failure and lead conversion, with honest confidence intervals.
Planning decisions
AI automation
Removing the manual step between two systems - reading, deciding, writing back into your ERP or CRM.
Repetitive handoffs
How an AI build runs
From a business problem to a measured outcome.
Every engagement starts with a process that costs money and ends with the same number, measured again. The model is the middle, not the point.
Problem
We start from a business process with a measurable cost, not from a model.
Data
Auditing what data exists, where it lives, and what it can honestly support.
Intelligence
Retrieval, fine-tuning, classical ML or an agent - whichever the problem needs.
Action
The model writes back into real systems: your ERP, CRM, tickets or devices.
Outcome
Measured against the original number, then tuned in production.
Stack
What we build it with.
Where it gets used
Document intelligence
Contracts, invoices and reports read and structured at volume.
Support automation
Triage, drafted replies and escalation with a human in the loop.
Forecasting
Demand, inventory and capacity planning inside an ERP.
Quality inspection
Vision models on the line, flagging defects in real time.
AI-powered SaaS
Intelligence as a feature in your own product, priced and metered.
Questions we get asked.
What kind of AI products does Repozitory build?
Generative AI applications, AI agents, RAG systems over private data, LLM-backed features, chatbots, NLP pipelines, computer vision models, predictive models and AI automation workflows.
Do you build on existing models or train your own?
Both. Most business problems are solved fastest with retrieval and orchestration over a strong general model. Where the task is narrow, repetitive and data-rich, a smaller trained or fine-tuned model is cheaper and more reliable.
Can AI be added to a system we already run?
Usually yes. Most of our AI work sits alongside an existing ERP, CRM or platform rather than replacing it - the integration and the data contract are the real work.
Have an idea worth building?
Whether it's an AI product, a software platform or a connected electronic device, let's turn your idea into something real.