AI Agents & Data
AI agent development for work your team should not be doing by hand
We design and build AI agents that read, decide and act inside the tools you already use: your CRM, ERP, inbox, ticketing system and databases. They handle the repetitive work, and they hand anything unusual to a person.
- 01Customer service agents
- 02Document processing agents
- 03Back-office workflow agents
- 04Sales and CRM agents
- 05Internal knowledge agents
- 06Microsoft Copilot Studio agents
- 07Agent monitoring and evaluation
At a glance
AI agent development means building software that reads a request, looks up the facts, decides what to do and then takes the action in your systems, such as updating an order or posting an invoice. It suits companies with repetitive, rule-based work in customer service, documents or back-office tasks. Tag4 Technology Solutions builds these agents with narrow permissions, full logging and human approval for risky actions.
Updated
- Best for
- Frequent, rule-based work like invoice entry, inbox triage and order status questions
- Typical timeline
- 4 to 10 weeks for a focused first agent to reach production
- Typical budget
- Tens of thousands of dollars for a one-workflow pilot; more for multi-system agents
- Core technologies
- Anthropic Claude, OpenAI, Azure OpenAI, Copilot Studio, MCP, LangGraph
- What you get
- A tested agent with step-by-step logs, approval steps and a monitoring dashboard
- Offices
- New York, Chicago, Dallas, Toronto, Sydney, Dubai
An AI agent is software that can understand a request, look things up, decide what to do and then take the action: update the order, draft the reply, file the invoice, open the ticket. The difference from a chatbot is that last step. A chatbot talks. An agent does the work and leaves a record of what it did.
The best first agents are boring on purpose. Think of the work that fills someone's morning: reading supplier invoices and keying them into Business Central, triaging a shared inbox, answering "where is my order" from the data in your system, or chasing missing documents from customers. These tasks follow rules most of the time, and the exceptions are easy to spot. That makes them a good match for an agent that does the routine cases and routes the odd ones to a person.
Where agent projects go wrong is predictable. Teams give the agent too much freedom too early, connect it to production data without limits, skip the test set, and then cannot explain why it did something. We work the other way around. Each agent gets a narrow job, the smallest set of permissions it needs, a written list of actions it may take, and a test suite of real examples it must pass before it touches live data. Every step is logged, so you can see what it read, what it decided and why.
A focused first agent usually takes 4 to 10 weeks to reach production, depending on how many systems it needs to connect to and how clean the data is. We start with a short discovery to pick a use case where the savings are easy to measure, build a pilot on a slice of real work, and only widen its scope once the numbers hold up.
What we do
AI Agent Development services
Customer service agents
Agents that answer questions on your site, in email or in chat using your own policies and order data, and pass the conversation to a person with a full summary when they should.
Document processing agents
Read invoices, purchase orders, claims, contracts and forms, pull out the fields you need, check them against your records and post them to your ERP or database.
Back-office workflow agents
Handle multi-step tasks like onboarding a customer, reconciling a statement or chasing overdue paperwork, following the same rules your staff follow.
Sales and CRM agents
Research inbound leads, enrich records in Dynamics 365 or HubSpot, draft first replies and keep the pipeline tidy so salespeople spend their time talking to buyers.
Internal knowledge agents
Give staff one place to ask questions across SharePoint, Confluence, Google Drive and your ticket history, with answers that cite the source document.
Microsoft Copilot Studio agents
For companies on Microsoft 365 and Dynamics 365, we build agents in Copilot Studio that work inside Teams and use your existing security and permissions.
Agent monitoring and evaluation
Dashboards that show what each agent handled, how often it escalated, where it made mistakes and what it costs to run, plus test suites that run on every change.
How we work
What you can expect from us
One job, clear limits
Each agent gets a narrow task, read-only access where possible, and an explicit list of actions it may take. Anything outside that list goes to a person.
Tested on your real work
Before launch, the agent has to pass a set of real past cases from your business. We rerun that set every time we change a prompt, a model or a tool.
Humans stay in charge
You decide which actions need approval. Early on that is most of them. As the agent proves itself, you can let it act alone on the routine cases.
Not tied to one AI vendor
We build on OpenAI, Anthropic Claude, Azure OpenAI or open-weight models, and structure the code so you can switch models when prices or quality change.
Tools and platforms
- Anthropic Claude
- OpenAI
- Azure OpenAI
- Microsoft Copilot Studio
- Model Context Protocol (MCP)
- LangGraph
- Python
- TypeScript
- PostgreSQL + pgvector
- Azure AI Search
- Power Automate
- Dynamics 365 / Dataverse
Process
From first call to production
Discovery
A few working sessions to pin down goals, users, constraints and what "done" means. You get a written scope and estimate.
Design
Architecture, data model and clickable UI before heavy coding starts, so surprises show up early and cheaply.
Build
Two-week sprints with a demo at the end of each one. You see working software, not status reports.
Launch
Automated tests, staged rollout, monitoring and a rollback plan. Go-live should be boring.
Support
Bug fixes, updates and new features on a monthly plan, or a clean handover to your team.
FAQ
AI Agent Development: common questions
What is the difference between an AI agent and a chatbot?
A chatbot answers questions. An AI agent can also take actions in your systems, such as updating a record, sending a reply or creating a ticket. That makes agents more useful, and it is also why permissions, logging and approval steps matter so much more.
How much does it cost to build an AI agent?
A focused pilot for one workflow usually costs in the tens of thousands of dollars, and a production agent connected to several systems costs more. Running costs depend on volume and the model used, and we estimate them up front so you can compare them with the time the agent saves.
Is our data safe with an AI agent?
We use business API terms where providers do not train on your data, keep data in your cloud where possible, and give the agent only the access its job requires. For sensitive data we can use Azure OpenAI in your own tenant or a self-hosted model.
What happens when the agent gets something wrong?
It will sometimes, so we plan for it. Risky actions need human approval, every step is logged so mistakes are easy to trace, and each fix is added to the test set so the same error does not come back.
Can an AI agent work with Dynamics 365, Salesforce or our own software?
Yes. Agents connect through the same APIs any integration would use. We connect agents to Dynamics 365, Business Central, common CRMs, help desks, email and custom databases, and we can add an API to older systems that do not have one.
How do we choose the first process to automate?
Pick work that is frequent, mostly rule-based and easy to measure, like invoice entry or order status questions. In discovery we look at a few candidates with you and pick the one with the clearest payback and the lowest risk.
Related
Often paired with
Generative AI Development
LLM apps, RAG over company documents and AI agents, tested with evals and kept within budget.
Learn morePower Platform
Power Apps, Power Automate, Power BI, Copilot Studio and Dataverse, with the governance to keep them maintainable.
Learn moreAPI Development & Integration
REST and GraphQL APIs, plus integrations between ERPs, CRMs, payment providers and SaaS tools.
Learn moreIndustries we build for
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