AI integration servicesfor the stack you already pay for.
We connect AI to the systems your team already works in: the CRM, the shared inbox, the document folder, the phone line, the accounting tool. It reads, sorts, drafts and routes inside those systems, and a person approves anything that matters before it goes out.
Scope sheet
- Scope to live
- 7 to 30 days
- Runs in
- Your accounts, on your data
- Before a customer sees it
- A person approves it
- You keep
- Prompts, code, logs and a runbook
- Starts with
- Free AI Opportunity Assessment
Where it breaks
Most AI projectsstall at the integration.
A model on its own is a demo. The value shows up when it can read the ticket, look up the customer in the CRM, check the contract in the shared drive and write its answer back to the place your team already looks. That connective work is where most AI projects stall, because it is plumbing, permissions and edge cases rather than prompts.
The other failure is the opposite one: a tool that acts with nobody watching. It sends the wrong quote or updates the wrong record, and nobody finds out until a customer does. An integration worth running logs every action, knows when it is unsure, and hands the decision to a person when the stakes call for one.
So we build the plumbing first, in accounts you own, and add the model once the data it needs is reachable and clean.
What gets built
Line by line,in accounts you own.
Each item is a line on the written scope. Take the ones the operation needs and leave the rest.
Document and email intake
Incoming email, PDFs and forms read, classified and turned into structured records in the system that should hold them, with the original attached.
CRM enrichment and triage
New leads and tickets sorted by fit and urgency, matched to existing records, and routed to the right owner with a short note on why.
Drafting with approval
Replies, quotes and follow-ups drafted from your own templates and data, queued for a person to approve, edit or reject before anything is sent.
Search over your own files
Answers pulled from your policies, price lists and past work, each one pointing to its source so your team can check it.
Voice and chat front doors
Agents that answer and qualify, then write the conversation into the CRM. They have their own page, linked below.
Guardrails and logging
Every model call recorded with its input, its output and the action taken. Uncertain cases go to a person, and failures raise an alert.
How it runs
From the first callto a running system.
Days 1 to 3
Map the work
We sit with the people doing the task today and list every system it touches, every decision in it, and where the data lives.
Week 1
Connect the systems
Access, permissions and data flows set up in your accounts. No model is involved until the right data can reach it.
Weeks 2 to 3
Add the model behind a person
The AI step goes in behind an approval queue. We compare its output with what your team would have done and tune it until the gap is small enough to trust.
Week 4 onward
Hand over, then widen
You get the runbook, the logs and a named owner on your side. Approval steps are relaxed one at a time, and only where the record shows it is safe.
Fit
Who this suits,and who it does not.
A good fit
- Your team re-types information from one system into another every week
- You get a steady flow of emails, forms or documents that follow a pattern
- You already pay for a CRM, help desk or ERP and want more out of it
- Someone on your side can own the process once it is live
Probably not a fit
- You want an AI strategy deck rather than something running in the business
- The process changes every week and nobody can describe it yet
- You need a custom model trained from scratch. We connect proven models to your systems
Frequently asked
Questions buyers askbefore the first call.
What does AI integration involve?
Connecting a language model to the systems where your work already happens, so it can read from them and write back to them. Most of the effort is access, data cleanup, permissions and error handling. The model is usually the smallest part of the build.
Which AI models do you use?
We pick per job and per data policy. That can be a hosted model from a major provider, or a setup that keeps the data inside your own cloud account. The choice is written into the spec with the reason, so it can be changed later without a rebuild.
Will our data be used to train someone else's model?
Not with the setups we use. We work through business tiers and APIs that do not train on customer data by default, and we document where each piece of data goes before anything is connected.
What happens when the AI gets something wrong?
It will, so the build assumes it. Uncertain cases go to a person, every action is logged with its inputs, and anything customer-facing starts behind an approval step. You can see what it did and why, and reverse it.
Does AI integration mean new software?
Rarely. The model connects to the tools you already run through their APIs, and its work shows up inside those tools, so your team keeps the screens it knows. New software gets built only for a gap the existing tools cannot close.
The offer
Free AIOpportunity Assessment.
We walk your operation, find the work still being done by hand, and tell you which of it is worth automating first. You keep the list whether or not you build with us.
- Takes
- 30 minutes
- Costs
- No cost, no obligation
- You get
- A written opportunity list
- Back in
- Three business days
01
Where the hours actually go
A short walk through the steps somebody repeats every week, and what each one costs you in time.
02
What AI can hold, and what it cannot
An honest split. Some of this work should be automated, some should be fixed by changing the process, and some should be left alone.
03
A build order with rough numbers
The opportunities ranked by return, with an estimate of hours saved and what each build takes to stand up.