Service 03 · Custom AI tools and agents
AI assistants built for one job, done well.
When off-the-shelf tools don't fit, we build focused AI assistants and agents that work from your documents and systems, with clear limits and a person in the loop.
- Who it's forTeams with a specific jobthat generic chat tools don't handle well
- What you getA working, tested toolwith guardrails, logs and documentation
- ApproachPrototype, measure, then roll outno big-bang launches
- PricingFixed-scope quoteAfter a free 30-minute call
Anatomy of a useful AI assistant
Six parts, and the model is only one of them.
Most of the work in a reliable AI tool is around the model: what it can read, what it can do, and what stops it from doing the wrong thing.
The model
The AI engine that reads and writes. We choose it per task, weighing quality, cost, speed and the vendor's data terms.
Your knowledge
The documents, procedures and records it's allowed to use, so answers come from your business rather than the internet.
Tools
Specific actions it can take, like looking up an order or creating a draft, each with limited permissions.
Guardrails
Rules enforced in code, not just in instructions: what it may never say, send or change.
Human checkpoint
Where a person reviews, edits or approves before anything reaches a customer or a system of record.
Logs and review
A record of questions, sources and actions, so you can check quality and improve it over time.
Examples
Jobs AI tools handle well.
Each of these works best with a clear scope and a person reviewing the output, at least at first.
- Knowledge
Internal Q&A assistant
Answers staff questions from your procedures and policies, and shows where the answer came from.
- Documents
Document intake
Reads PDFs, forms and emails, pulls out the fields you need, and flags anything it isn't sure about.
- Email
Triage and drafting
Sorts incoming messages, suggests who should handle them, and drafts replies for review.
- Sales
Proposal first drafts
Builds a first draft from your templates, price lists and the notes from a call.
- Meetings
Call and meeting notes
Summaries and next steps written into your CRM or project tool, ready for a quick check.
- Customers
Routine questions
Answers common customer questions by chat, text or email, with an easy hand-off to a person.
How we build it
Measured before it's trusted.
- Step 1
Define the job
What it should do, what it must never do, and what "good" looks like.
- Step 2
Prototype
A working version tried against real (or realistic) examples from your business.
- Step 3
Evaluate
We build a set of test cases and check accuracy before and after each change.
- Step 4
Pilot
A small group uses it on real work, with review on every output.
- Step 5
Roll out
Wider use, monitoring, and a plan for keeping it accurate as things change.
What we will and won't build
What we build
- The job is specific and repeated often.
- There's a clear source of truth to answer from.
- A person can review the output, at least at first.
- You can tell us what a good answer looks like.
What we won't build
- It would make final decisions about people, such as credit, hiring or medical care, without human review.
- Customers couldn't reach a person when they need one.
- It needs data you aren't allowed to share with an AI provider.
FAQ
Questions we hear.
Which AI model do you use?
There isn't one right answer. We pick per task, weighing quality, cost, speed and the provider's data-handling terms, and we keep tools easy to switch if a better option appears.
Will our data be used to train someone else's AI?
That depends on the provider and the plan. We review the data terms with you and use business or API offerings whose terms fit your requirements. If a use can't meet them, we don't build it that way.
How do you stop it from making things up?
No AI is perfect, so we design around that: answers come from your approved sources, the tool shows where an answer came from, checks in code block risky output, and people review what matters.
What's the difference between an assistant and an agent?
An assistant answers or drafts when asked. An agent can also take steps on its own, like looking something up and then updating a record. Agents need tighter permissions and more checkpoints, so we start narrow.
Insights
Further reading.
- Build vs buy: how to decide on AI tools Buying is usually faster. Building is sometimes necessary. Here's how to tell which situation you're in. Read the article
- How to choose an AI vendor or LLM provider Demos all look great. Data terms, real-world accuracy and exit options are where vendors differ. Read the article
- AI risk and compliance basics for mid-sized businesses You don't need a compliance department to use AI responsibly. You need to know the main risks and a few sensible controls. Read the article
Free 30-minute call
Find out where AI can help your business.
Tell us how your team works today. We'll tell you plainly where technology can save time, where it can't, and what a sensible first step would be.
Prefer the phone? Call (949) 691-0086