AI Solutions
We connect large language models (LLMs) to your company's data and processes: RAG systems that answer from your documents, AI agents that carry out workflows, and automations that cut down repetitive work.
AI projects
What's included
LLM Agents and Assistants
AI agents that work with your company data and rules and, where needed, take actions in your other systems.
RAG and Document Search
Systems that search your internal guides, contracts and PDFs according to each user's permissions and show the source with every answer.
AI Workflow Automation
Integrations that use AI to automate data extraction, content drafting and email workflows.
AI Features in Your Apps
We add features such as image recognition, summaries, classification and chat to your web and mobile apps.
Quality and Cost Tracking
We measure answer quality against sample question sets, track token usage and cost, and improve weak answers through feedback.
Questions
How do you protect our confidential data?
OpenAI and Anthropic state that, by default, they do not use data sent through their APIs to train their models. On our side, we send the model only the data it needs, limit access by permission and agree with you up front where any personal data may go. If data must not leave your company, we look at open-source models running on your own servers.
What happens if the AI gives a wrong answer?
Language models can make mistakes. So we ground answers in your source documents, have the system hand uncertain cases to a person, and keep the final approval for critical actions with your team.
Why a custom integration instead of plain ChatGPT?
ChatGPT is a general-purpose tool that works without knowing your permissions, workflows or systems. A custom integration ties the model to your own data and business rules and writes the results straight into your ERP, CRM or helpdesk.
What documents can we feed into the system?
PDF manuals, Word and text files, Notion pages, FAQ lists or database tables. We split and index them into a searchable vector store; there is no minimum, and even a few hundred pages make a useful start.
How long does an AI project take?
It depends on scope. A pilot focused on a single workflow usually works within 3–6 weeks, like an MVP; larger systems can take 2–4 months. After a discovery call we share a clear timeline and a transparent quote.
Related guides
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What Is RAG? Building an AI Assistant for Company Documents
What is RAG and how does it work? Learn how retrieval-augmented generation powers an AI assistant that answers from your company documents with sources.
AI Agents for Business Process Automation: A Practical Guide
What are AI agents and how do they automate business processes? Learn agent architecture, real use cases, risks and how to roll them out safely in your company.
AI Chatbot for Customer Service: Website and WhatsApp Setup
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