AI
Intelligence that works alongside you.
Assistants, agents, and knowledge systems that work from your own documents and tools.
Put AI where it actually helps.
We build AI for one specific job at a time. It answers from your own information and shows where each answer came from. Decisions stay with your people.
- An assistant
- Answers questions and drafts documents.
- An agent
- Carries out steps across your tools and stops for a person when it should.
- A knowledge system
- Organizes what your organization knows so people and AI can find it.
What we build
Pick the one closest to your work.
Answers from your SOPs
Operations and field teams
An assistant staff can ask, at a desk or on site, about SOPs, equipment manuals, and safety procedures. Each answer links to its source.
What changesExperienced staff get interrupted less.
Support reply drafts
Customer support
Drafts replies from your help center and past tickets. A support rep edits and sends each one.
What changesReps spend their time on the tricky tickets.
Proposal first drafts
Professional services
Assembles a first draft from your past proposals, service descriptions, and team bios.
What changesYour team skips the boilerplate and goes straight to pricing.
Shipping document intake
Logistics
An agent that reads bills of lading and packing lists, pulls out the key fields, and enters them in your system.
What changesStaff check only the fields the agent marks as uncertain.
Sales call briefs
Sales
A one-page brief before each call, built from your CRM notes, recent emails, and the prospect’s website.
What changesReps walk in prepared without digging through tabs.
Signs AI could help
- The same questions keep landing on the same few people.
- The answer exists, but it’s buried in shared drives and inboxes.
- Replies and proposals follow a pattern, yet each one starts from blank.
- Skilled people copy fields out of documents by hand.
Today
- Bills of lading and packing lists arrive as PDFs and scans.
- Someone retypes shipper, consignee, weights, and container numbers.
- Typos surface later, when a shipment is already moving.
With the system
- The agent reads each document as it arrives.
- It fills the fields and marks any it isn’t sure about.
- Uncertain fields go to a coordinator to confirm. A person decides
- Confirmed records are saved, with a link to the source file.
What stays human: Anything the agent isn’t sure of, and every exception, is decided by a person.
An illustration of the kind of work we do, not a client story.
How we work
Step 1: Pick one job.
A specific task where AI can help and a person can easily check the result. If a task isn’t a good fit, we’ll say so.
Step 2: Prepare the knowledge.
We gather the documents the system will use, flag what’s out of date, and set what it can and can’t see.
Step 3: Test on real questions.
We use your team’s own examples, including the awkward ones. Before anyone relies on it, we agree how to judge whether it’s working.
Step 4: Launch with a person in the loop.
It goes live with review points and a simple way to report a bad answer.
Questions worth asking
01Will our data be used to train someone else’s AI?
Where possible, we use business-grade AI services whose terms say your data isn’t used for training. Each system sees only the information it needs. If your data must stay in a particular region or environment, tell us early.
02Which AI models do you use?
Whichever fits the job, based on accuracy, cost, and your privacy requirements. We aren’t tied to one vendor, so the system can switch if a better option appears.
03What happens when it gets something wrong?
It will, sometimes, so we design for it. Answers cite their sources. Uncertain cases go to a person. Anything with real consequences, such as a customer reply or a payment, needs a person to approve it.
04Do we need to get our documents in order first?
No. Sorting out what’s current, duplicated, or missing is part of the work. If there are serious gaps, we’ll tell you before building on top of them.
05What does it cost?
It depends on the scope, so we don’t publish prices. We start with a short discovery phase to check the idea is worth building. You’ll get a written estimate before any build work, including monthly running costs such as AI model usage.
Start with one useful job.
Tell us about a question your team answers every day. We’ll tell you whether AI is the right fit.