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SERVICE · AI AGENTS

AI agent development for real work inside your systems.

Seamwire builds AI agents for mid-size companies: software that does real work inside your systems, not a chatbot on the side. Our agents read documents and emails, look things up in your ERP and CRM, update records and draft replies, and they hand anything that matters to a person for approval. Each agent has narrow permissions, logs every action and runs on model providers you approve, and you own the code and data.

Start with a 10-day first stepCustom software & internal tools
FIRST STEP
10 working daysOne process, mapped and shown working, with a business case and a dated plan.
TEAM
3–5 peopleA dedicated team from our 50+. The people who scope it build it.
OWNERSHIP
YoursCode, data and accounts are yours from the first commit. No lock-in.
01

SIGNS YOU NEED THIS

  1. 01Your team reads the same kinds of documents all day and types what they find into a system.
  2. 02Customer and supplier emails wait because answering means looking in three places.
  3. 03You have a chatbot, but it can only talk; it cannot do anything in your systems.
  4. 04An AI pilot impressed in a demo and never reached production.
  5. 05Leadership wants AI in operations, and nobody can say where it is safe to start.
  6. 06Worries about data privacy have stopped AI projects before they began.
02

WHAT WE BUILD · AI AGENT DEVELOPMENT

03

SYSTEMS AND TOOLS WE COMMONLY WORK WITH

MODELS
  • Anthropic Claude
  • OpenAI GPT models
  • Google Gemini
  • Azure OpenAI
  • AWS Bedrock
  • open-weight models (Llama, Mistral)
AGENT TOOLING
  • Model Context Protocol (MCP)
  • Claude Agent SDK
  • OpenAI Agents SDK
  • LangGraph
  • pgvector search
SYSTEMS AGENTS WORK IN
  • SAP Business One
  • Dynamics 365
  • NetSuite
  • Odoo
  • Salesforce
  • HubSpot
  • Microsoft 365
  • Google Workspace
WHERE THEY RUN
  • your AWS, Azure or Google Cloud account
  • PostgreSQL
  • queues and schedulers

We pick tools for your situation, not ours. If something you already run does the job, we keep it.

04

HOW IT WORKS

  1. 01

    A 10-day first step

    One process or page, mapped with the people who do the work and shown working. You leave with a business case and a dated plan, and keep everything it produced.

  2. 02

    Build in short, visible steps

    Working software every week or two on a staging site you can click, with weekly written notes on what moved and what we need from you.

  3. 03

    Launch and hand over

    Released carefully, with monitoring switched on, then a handover pack: code, docs, runbooks and a session with your team.

  4. 04

    Look after it

    Support, monitoring and improvements on terms agreed in writing before we start, with a named team who knows the work.

The full approach, phase by phase
05

WHERE WE DO THIS MOST

01ManufacturingTYPICAL FIRST STEPConnect one line's output to your stock figures, so what you promise matches what you can make.02Logistics & supply chainTYPICAL FIRST STEPWire your dock scans to customer tracking, so “where is it?” answers itself.04HealthcareTYPICAL FIRST STEPAutomate confirmations and reminders for one clinic, so the day's list is right before the doors open.06Professional & financial servicesTYPICAL FIRST STEPTake one intake process from inbox to filed and approved, with every step logged.07Ports: shipping & freight forwardingTYPICAL FIRST STEPPull your carriers' milestone updates into one timeline, so every ETA your customer sees is the latest one.
06

QUESTIONS BUYERS ASK

What is the difference between an AI agent, a chatbot and an automation?
A chatbot answers questions in a conversation and usually cannot change anything. An automation follows fixed rules: when this happens, do that. An AI agent is given a goal and a set of tools, reads unstructured input such as emails and documents, decides which steps to take, and acts in your systems within limits you set. We use the simplest one that does the job; often the best answer is an automation with one agent step inside it.
How do you stop an agent doing something wrong?
Agents get only the permissions their job needs, often read-only to begin with. Actions that matter, such as writing to a customer, changing a price or posting above a value you set, wait for a person to approve. Inputs and outputs are checked against your rules, every action is logged with its sources, and any agent can be paused at once. Permissions widen only when the logs show the agent has earned it.
Is our data private, and which AI models do you use?
We work with providers such as Anthropic, OpenAI and Google, directly or through Azure, AWS Bedrock or Google Cloud, and with open-weight models where they fit. We use business and API terms that keep your data out of model training where the provider offers that, and agents can run inside your own cloud account and region. Only the data a task needs is sent, sensitive fields can be masked, and a DPA and NDA come before any access.
What drives the running cost of an AI agent?
Mainly how many tasks it handles, how much text each task involves, and which model it uses, since larger models cost more per task than smaller ones. Hosting, the systems it calls and the share of tasks that need a person also count. We design to keep it down, with smaller models for simple steps, plain rules where AI is not needed and repeated work cached, and we show running cost per task on a dashboard.
What should our first AI agent do?
Pick a task that is frequent, mostly reading and looking things up, easy for a person to check, and costly only in time if it goes wrong. Reading supplier invoices into the ERP or drafting replies to order-status emails are good examples. The 10-day first step maps the task with your team, runs the agent on real past cases, and gives you a business case before anything touches live systems.
Can an agent work with our ERP and CRM?
Yes, and that is where agents earn their place. They connect through the system's API, an integration layer we build, or a Model Context Protocol (MCP) server that exposes only the actions you approve. If a system has no API, we find another reliable way in. Each agent works under its own account, so every change it makes shows in the system's own audit trail.
How do you know the agent is accurate enough?
Before launch we test it against a set of real past cases with known right answers, and agree with you the accuracy it must reach for each kind of task. In production we track how often people approve, edit or reject its work, and review every mistake. When a model or your process changes, the same tests run again before anything is updated.
07

GUIDES

01How to replace spreadsheets with custom software (without stopping the business)HOW TO · 6 MINWhen a spreadsheet has become a critical system, how to replace it with a custom tool safely: what to copy first, how to run both side by side, and how to move the data without losing anything.02Build or buy: when a custom internal tool beats off-the-shelf softwareDECISION · 5 MINA practical way to decide between buying software and building a custom internal tool: the questions to ask, the hidden costs on both sides, and when a hybrid (buy, then connect) is the best answer.03How to choose a custom software development company: 12 questions to askCHECKLIST · 6 MINTwelve questions to ask before hiring a custom software development company or agency, from who owns the code to how they handle security, handover and what happens after launch.

YOUR FIRST STEP

Start with one process, working in ten days.

Tell us where it slows down. We map it with your team, show it working, and hand you a business case. If the numbers do not work, you keep everything it produced.

Tell us where it slows down