MindYards helps mid-market and enterprise teams turn AI into dependable products, agents and day-to-day operations. Six service lines, one accountable team, fixed scopes with written outcomes.
Most AI programmes fail between the phases: strategy that never gets built, builds nobody operates, operations nobody governs. We cover all six so nothing falls between vendors.
GenAI and LLM applications, custom ML models, enterprise integration and the cloud infrastructure underneath. The largest part of what we do.
Agents that plan, call tools and complete work inside your real processes, with the observability and guardrails to run them safely.
We keep models, agents and LLM workloads accurate, affordable and compliant after launch, on a monthly retainer with SLAs.
Roadmaps, prioritised use cases and leadership advisory that end in decisions and budgets, not slide decks.
Deadline-driven, audit-ready work for regulated sectors: EU AI Act, NIST AI RMF, ISO 42001, model risk and red-teaming.
The foundations AI depends on: usable data, trained people, redesigned workflows and analytics that leaders actually read.
Pick one repeatable process, move four sliders, and see the hours freed, the value per year and the engagement model that fits. Then run the eight-question readiness check.
Try the estimatorWe work deeply in the Microsoft and Salesforce ecosystems, stay vendor-agnostic on models, and deploy on-premises or in-country when the data demands it.
Short, practical notes from our engagements. One or two a month.
The first invoice after launch is usually a surprise. Here is where the money goes in a typical LLM workload and the five changes that recover most of it.
Read"We tested it" can mean anything from a few prompts in a playground to a suite that blocks bad releases. Here is what the second kind looks like, piece by piece.
ReadMost agent projects stall for reasons that were visible on day one. Here are the five questions we ask in the first meeting, and what a good answer sounds like.
ReadEvery engagement follows the same four moves. It keeps risk low for you and keeps us accountable for what is working.
Agree the business outcome, the metric and what good enough looks like before any code is written.
A working slice on your real data in weeks, not quarters, with an evaluation set you can inspect.
Guardrails, monitoring, cost controls, compliance evidence and fallbacks so the system behaves in production.
Your team owns it with documentation and training, or we keep running it under a managed retainer.
A 30-minute call, no deck, no obligation.
