Practice/AI & Automation

AI &Automation

We build AI that does actual work: narrow, measured, accountable systems that sit inside your operations rather than beside them.

01

Frame

Week 1–2

Process mapping, data access, definition of done.

02

Prototype

Week 3–5

One narrow workflow, measured against the manual baseline.

03

Harden

Week 6–9

Evaluations, guardrails, audit trail, human approval paths.

04

Operate

Ongoing

Monitoring, cost control, incremental scope expansion.

01Approach

Most AI projects fail on process, not on models. So we start with the process.

We map how the work is done today, where judgement is genuinely required, and where the cost sits. Only then do we decide what should be automated — and what should deliberately stay manual.

The result is a small number of well-instrumented systems rather than a broad layer of demos. Each one has an owner, a baseline, and a number attached to it.

02Capabilities

Four areas, usually delivered in combination.

01

AI agents & chatbots

Agents and chatbots that handle defined workflows end to end — quoting, qualification, document handling and exception triage — with every action written to an audit trail.

  • AI agents
  • Chatbots
  • Approval paths
02

Assistants

Assistants grounded in your own documents, contracts and tickets, scoped by permission so each team sees only what it should.

  • Internal assistants
  • Retrieval
  • Source citation
03

Sales & support automation

Connected workflows that remove manual steps from lead handling, customer support and the systems between them.

  • Sales automation
  • Support automation
  • Integrations
04

Business process automation

Before a process reaches production it is measured against a manual baseline, then monitored for quality, latency and cost.

  • Process automation
  • Guardrails
  • Reporting
03In practice

Drafted by agents. Approved by people.

A typical architecture: existing systems of record feed an orchestration layer, which proposes actions and routes anything consequential to a human before it commits.

EngagementRetained, 6 months +
Team2–4 specialists
Starting pointTwo-week framing
DeploymentYour cloud or ours
SOURCESORCHESTRATIONSURFACESERPWMSCRMAgentsPolicyEvaluationAudit trailHUMAN REVIEWOps consolePartner APIFIG. 01OPERATIONS LAYERREV. 03
Next step

Start with one workflow.

Send us the process that costs you the most time. We will tell you honestly whether AI is the right instrument for it.