Your first AI agent in production in 30 days. Fixed scope, fixed price.
AI agent use cases

AI agents for sales prospecting.

Turn prospect research, qualification, outreach preparation and record-keeping into one governed workflow, while the sales team keeps control of everything that leaves the company.

A sales team reviewing prospect research prepared for approval.

Where an agent can contribute

Depending on the workflow, an agent may support:

  • Collecting approved public and company context
  • Applying defined qualification criteria
  • Preparing prospect research summaries
  • Preparing first-draft outreach against approved messaging rules
  • Flagging uncertainty or conflicting information for review
  • Preparing the workflow and record updates
  • Escalating sensitive or ambiguous accounts
  • Holding for sales approval before anything goes out

The goal is a better prospecting workflow.

A useful implementation looks at the whole path: identifying a prospect, qualifying, preparing, approving, reaching out, and keeping the record straight.

The agent should remove unnecessary manual preparation without taking ownership away from the sales team. Faster drafting is a step. Inbound lead to booked meeting is a workflow.

What could be measured

Illustrative KPI types, not promised results. The baseline and the success measure are agreed for your real workflow before implementation.

  • Research time per prospect
  • Prospects prepared per rep
  • Sales approval rate
  • Response rate
  • Meetings booked
  • Process and CRM completeness
  • Rework or edit rate
  • Escalation rate

Questions about this workflow.

Does the agent send messages without sales approval?

Not without approval on the early runs. A person approves every real action, the agent runs in a sandbox first, and escalation rules are agreed before go-live. If it is unsure, it stops and asks.

The approval gates loosen only when you decide you are comfortable, not before.

Can the agent qualify prospects?

It can apply the qualification criteria you define, and prepare the evidence for each judgement so a person can check it.

What it does not do is decide which criteria matter. That is a commercial decision with an owner.

How do you measure value?

Against a baseline captured before the agent goes live. We measure the workflow before the agent touches it, and we treat that as a gate.

Nobody can reconstruct the before afterwards, which is why most AI work inside most companies cannot be defended, funded or repeated.

Find where AI can create measurable value first.

Next day you get a one-page map of where an agent pays first, the metric we'd aim to move, and a fixed price and date.

45 minutes. You keep the map either way.

No preparation required. No commitment.