AI Integration & Automation
AI wired into the inbox, the phone, the CRM and the calendar, with boundaries and a person in the loop — and the hours it saves, counted.
AI is only useful once it is wired into the work
Most businesses have already tried AI. Someone pasted a customer email into a chat window, got a decent draft, and pasted it back. That is a demo, not a system. The gap between the two is integration: the model has to be connected to the inbox, the calendar, the CRM, the phone line, and the records it needs, and it has to hand its work to a person at the right moment. That wiring is the job, and it is where most AI projects quietly stall.
We build the wiring. An integration project starts by naming one workflow that costs real hours — triaging web leads, answering the same thirty questions, drafting quotes from a call, chasing invoices — and ends with that workflow running on its own, logged, and reviewable. Not a chatbot bolted to the corner of the site. A step in your process that now happens without anyone typing.
The model is the least interesting part. We choose it for the task and keep it replaceable, because the market changes every quarter and your system should not be married to one vendor's pricing. What lasts is the integration layer: the connections to your tools, the rules about what the AI may do alone and what it must hand off, and the record of every run.
Guardrails are designed in, not added after the first mistake. Every automated action has a boundary — draft but do not send, book but do not reschedule, answer but escalate on price — and every boundary is visible to the person who owns the outcome. A human review step is not a failure of automation; for anything that touches money or a customer, it is the point.
We also measure the thing you actually bought: hours. Each workflow reports how many runs it handled, how many it escalated, and how long a person would have spent. If the number is not there after the first month, we change the workflow or turn it off. AI that cannot show its work is a subscription, not a system.
This page is the umbrella. The pages beneath it go deeper on each piece — grounding a language model in your own documents, building agents that act on your behalf, and the workflow automations that carry data between tools without a person in the middle. Start here if you know the problem and not yet the shape of the answer.
WHAT WE CONNECT
The model, wired into the tools you already run
Inbox and forms
Every lead read, classified and routed the minute it lands, with a draft reply waiting for review.
Phone and SMS
After-hours calls and texts answered, qualified and booked, with a transcript in the CRM by morning.
CRM and records
The AI reads the customer's history before it answers and writes back what it did.
Scheduling
Appointments offered, confirmed and rescheduled against the real calendar, never a guess.
Boundaries built in
Draft-only, book-only, escalate-on-price. Each action has a limit and a person who owns it.
Hours, counted
Every run logged with what it handled, what it escalated and the time it saved.
Have one workflow that eats your week?
Name it. We will map where the AI plugs in, where a person stays in the loop, and what it saves — with a fixed price for the first automation.
THREE LENSES
Built to run, be checked, and be found
A step in your process
The automation lives where the work lives — the inbox, the CRM, the phone — not in a separate tab.
Reviewable by design
Logs, handoffs and boundaries mean a person can always see what the AI did and why.
Model-agnostic
The model is swappable; the integration layer is what you own and what keeps working.
From one painful workflow to a running system
Pick the workflow
One process with a clear start, a clear end and a real cost in hours. Not everything at once.
Map the boundaries
What the AI may do alone, what it hands off, and who sees the log. Agreed before a line is written.
Wire it in
Connect the model to the tools, build the handoffs, and run it alongside the current process.
Measure and expand
Read the first month's numbers, tune the rules, and pick the next workflow from what you learned.
Questions
Frequently asked
This is the umbrella. The LLM page is about grounding a model in your own documents so it answers from your facts; the agent page is about software that takes actions on your behalf; the automation pages are about moving data between tools. An integration project usually uses two or three of those, and this page is where you start when you know the problem but not yet the shape of the answer.
Whichever fits the task, and we keep it replaceable. The integration layer — the connections to your tools, the rules and the logs — is what you own. The model behind it can be swapped when a better or cheaper one appears, which happens every few months.
Boundaries set before it runs: draft but do not send, book but do not reschedule, escalate anything about price. Every action is logged, and anything that touches money or a customer relationship has a person in the loop by design. You define the limits; the system enforces them.
A single workflow — lead triage, after-hours booking, quote drafting — is a fixed-price project, typically in the low thousands, and it is priced after a short discovery call. Model usage is billed to your own account so you control it. Larger programs qualify for 0% financing.
Each workflow reports its runs, its escalations and the time a person would have spent. If the hours are not there after the first month, we change the workflow or turn it off. That number is in the monthly report, not in a sales deck.
Still have a question about AI Integration & Automation? Ask us directly — we answer straight.
Start the conversationStart now. Pay monthly. Add nothing for interest.
Put 25% down at signing and spread the rest in equal monthly payments. The total you pay is the price on the proposal.
- Up to 12 months on any project
- 24 months from $15,000
- 36 months from $20,000
Financed projects are hosted on the DataCram platform for the length of the plan.
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