AI that reaches production
Most AI projects stall at the pilot. We build agents, models and copilots into the systems your team already uses — and train the people who inherit them.
Most AI projects stall at the pilot. We build agents, models and copilots into the systems your team already uses — and train the people who inherit them.
Digistan Consultant builds AI agents for sales, service and operations; custom LLM and GPT solutions; MCP servers and RAG knowledge systems; voice agents, chatbots, computer vision, NLP and predictive analytics. It also provides AI strategy, readiness assessment, MLOps, governance and training.
The gap between an impressive demo and a system your team relies on by Tuesday is the entire problem. It is rarely the model. It is data that was never cleaned, a workflow nobody mapped, an integration that does not exist, and a team that was never taught to trust the output.
We work across four groups: agents and automation for the work itself, LLM and generative AI for the reasoning layer, applied AI for perception and prediction, and strategy and governance for everything that keeps it safe and maintainable. Most engagements draw on two or three.
Low-code and no-code agents for sales, service and operations, plus end-to-end workflow automation.
Read more6 servicesCustom LLM development, GPT solutions, MCP servers, RAG knowledge systems and generative content pipelines.
Read more6 servicesVoice agents, conversational AI, computer vision, NLP, predictive analytics and rapid MVP development.
Read more6 servicesConsulting, readiness assessment, data preparation, MLOps, responsible AI and training programmes.
Read moreA focused agent deployed into an existing workflow typically runs six to ten weeks from discovery to production. Larger platform work runs in quarters. We scope the first measurable outcome deliberately small so you see value before committing to the full roadmap.
Usually less than people fear. Many agent and RAG projects work from documents and existing systems rather than a warehouse. Where data genuinely blocks progress, we say so and start with a data readiness assessment instead of billing you for a model that cannot work.
Whichever fits the constraint. Commercial APIs where speed and quality matter, open-weight models where cost, privacy or on-premise deployment matter. We design so the model can be swapped without rewriting the system around it.
You do — code, prompts, configuration and documentation. We build so your team can operate and extend the system without us.
A discovery call is a working session on your constraint, not a sales pitch.
A short note is enough. You'll hear back from the team, not a bot — usually within one working day.
Answers go to the Digistan team. See our privacy policy.