AI & Automations · 03

AI inside the tools your team already uses.

AI that drafts inside your CRM, answers questions from your internal wiki, or triages your support inbox. Tested before it touches a customer.

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Abstract visualization suggesting AI inside business tools
Trust

AI that gives wrong answers costs you customers. We test before it goes live.

Whether it talks to customers or helps your internal team, an AI that gets facts wrong is a liability. We anchor it to documents you already have and keep a human in the loop for anything it is not sure about.

We measure fewer tickets and faster drafts, not how clever the demo looked.

01

Trained on your own documents.

Pricing tables, legal appendices, and product specs handled individually. Each doc type gets its own setup and review rules.

02

AI spend by department.

Each team has a spend limit. Finance sees a predictable line item, not a surprise cloud bill at month end.

03

Evaluation sets from real tickets.

We run past questions against every model or prompt change before it goes live. Quality does not drift quietly.

Execution detail

What this engagement includes in practice.

These are the checkpoints we sign off before the next phase ships. One named lead owns the lot.

01
Written policy on what the model can see, who approves outputs, and how long data is kept
02
AI embedded in CRM, helpdesk, or wiki with audit trail in one login
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Regression checks on real tickets before every prompt or model change goes live
FAQ

Questions leadership teams ask before they commit budget.

What is included in LLM inside existing tools?

A scoped read of how things work today, a written plan you can approve, and delivery checkpoints with one named lead. We do not hand you a deck and disappear.

How long does LLM inside existing tools usually take?

Most first delivery cycles run two to six weeks. Access to systems, decision speed, and any compliance sign-off are usually what moves the date.

How do you measure outcomes for LLM inside existing tools?

We agree the number before build starts: hours saved, error rate, conversion lift, uptime, or cost avoided. If we cannot name it, we do not scope it.

Who should be involved from our side?

One person who can say yes on budget and one person who knows how the work actually runs. That keeps decisions fast and handoffs short.

Concrete solution

Bring the operational risk.You get a clear diagnosis and a concrete next step.

Book a 15-minute operator call

We are the right fit if you want a team that pushes back when it matters.

Reviewing first?

Company evidenceon the site.

Engagements with commercial outcomes on Work. Team bios and operating model on About. Nothing to download. Review it before you commit to a call. Open to review. Commit when ready.