--- title: "Custom AI Agents and Model Training in New Hampshire | T10" url: "https://t10.net/services/custom-ai-agents-model-training/" description: "Custom AI agents and model training for New Hampshire businesses, connected to real systems and evaluated against measurable business tasks." lastmod: "2026-10-15" --- [All services](https://t10.net/#what-we-do)Build # Custom AI agents and model training in New Hampshire When no product fits the job, we build the agent your work needs. T10 builds agents around your documents, systems and decision points. If a product you can buy already does the job, we'll say so and set that up instead. When we build, we use the simplest reliable approach first, then fine-tune or train a model only when a well-defined task and strong examples show that custom training will produce a better result. [Discuss your AI plans](https://t10.net/#book) ![Illustration of a desk at dusk with a monitor showing documents, email and a database connected to an AI agent that ends in an approval check](https://t10.net/media/services/agents-hero-1200.webp) Custom does not mean complicated for its own sake. Every agent needs a defined job, evidence it can use, a measurable standard and a clear place to send exceptions. What changes ## A useful outcome, not another login. - An agent designed around a specific business task and operating environment - Connections to the approved documents and systems needed to do the work - Evaluation against representative examples before the agent is trusted - Human approval wherever money, safety, commitments or judgment are involved A working model ## A roofing estimate, drafted and waiting for you. A concept film of one agent we could build for a trade shop. It reads the walk-around photos and notes, drafts the job ticket with a price range, and sends nothing to the customer until the owner approves it. The house, address and jobs are made up. Example workflows ## Small enough to prove on real work. ![](https://t10.net/media/services/agents-operations.webp)01 ### Operations agents Read incoming requests, collect missing details, update approved systems and prepare the next action for a person to review. ![](https://t10.net/media/services/agents-knowledge.webp)02 ### Knowledge agents Find answers across policies, manuals, service history and product information while showing the source behind the response. ![](https://t10.net/media/services/agents-models.webp)03 ### Task-specific models Fine-tune or train for classification, extraction or other repeatable work when prompt-based approaches cannot meet a defined quality target. How an engagement works ## Four steps, and you see it work before you commit. 1. 01 ### Define the job Agree the task, the evidence the agent may use, what a correct result looks like and where exceptions go. 2. 02 ### Connect the data Connect the approved documents and business systems the agent needs, with permissions that match the people it serves. 3. 03 ### Evaluate Test against representative examples and success criteria before the agent is trusted; fine-tune or train a model only if evaluation shows it helps. 4. 04 ### Deploy and hand over Launch with human approval on consequential steps, then hand over the code, configuration and operating notes. A good first engagement ## What we look for before recommending an engagement. - The task occurs often and has a recognizable correct result - The agent needs access to business-specific information or systems - Representative examples exist for development and evaluation - There is a responsible owner for approvals, exceptions and ongoing quality Questions ## Custom AI agents and model training: straight answers. Could an existing product do this instead? Sometimes, and then we'll recommend it. Products such as Grok Bot handle a lot of routine work on websites and apps, and are much quicker to set up. A custom agent earns its place when the job touches sensitive systems, needs dependable behavior, or connects systems that no product covers well. Does every custom agent need a custom-trained model? No. Many useful agents combine a capable existing model with controlled business data, tools and workflow rules. We recommend training only when evaluation shows it solves a real limitation. How do you know whether the agent is reliable? We define representative test cases and success criteria before deployment, track failures and require handoff when evidence or confidence is weak. A polished demonstration is not a substitute for evaluation. What systems can a custom AI agent connect to? Most systems with an API or a reliable export: email, shared drives, CRMs, ERPs, ticketing and HR platforms. Our own assistants run on top of ServiceNow and Workday. Who owns the agent once it is built? You do. You receive the code, configuration and notes on how it runs, so nothing stops working the day you stop paying us. How much does a custom AI agent cost? The first 30-minute planning call is free. We usually start with a focused proof of concept on one task, scoped and quoted before work begins. ## Related services - [AI Cowork training](https://t10.net/services/ai-cowork-training/) - [Private GPU hosting](https://t10.net/services/private-gpu-hosting/) - [Grok Bot setup](https://t10.net/services/grok-bot-setup/) - [AI voice agents](https://t10.net/services/ai-voice-agents/) - [AI workflow discovery sprint](https://t10.net/services/ai-workflow-discovery-sprint/) - [AI approval dashboards](https://t10.net/services/ai-approval-dashboards/) - [Case studies](https://t10.net/projects/) ## Further reading - [Demystifying Agentic AI: Architectures vs. Workflows](https://t10.net/blog/demystifying-agentic-ai-architectures-vs-workflows/) - [How we built a small town website chatbot](https://t10.net/blog/how-we-built-asknbt10net-town-website-chatbot/) - [Vibe Checking: Revolutionizing AI Agent Testing Through Prompt-Driven Automation](https://t10.net/blog/vibe-checking-revolutionizing-ai-agent-testing-through-prompt-driven-automation/) - [From Hype to Hard-Won Truth: Why Pure Vector RAG Fails at Scale (and What Actually Works)](https://t10.net/blog/from-hype-to-hard-won-truth-why-pure-vector-rag-fails-at-scale-and-what-actually-works/) New Boston ยท Statewide ## Start with one practical need. [Book a free AI planning call](https://t10.net/#book)