Use Cases

AI Lead Qualification

Score and route incoming enquiries against your own criteria, with a written rationale attached.

Integrations

  • CRM
  • Telegram
  • Google Workspace
  • REST API

The task

Incoming enquiries arrive faster than anyone can properly assess them, so they are handled in the order they were received rather than in the order of their value. Good opportunities go cold while someone works through a queue that is mostly noise.

What it works from

  • Form submissions with the fields you already collect
  • Inbound email to a shared sales address
  • Campaign source, landing page and referrer data
  • Your existing CRM records for duplicate detection

The automated workflow

  1. The enquiry is received and normalised into a single structured record.
  2. It is checked against the CRM for an existing contact, account or open deal.
  3. Free-text is read to extract the stated need, scale indicators and timing.
  4. The enquiry is scored against your written qualification criteria.
  5. A short rationale is generated explaining the score in plain language.
  6. The record is created or updated in the CRM and assigned to an owner.
  7. A notification goes to the owner's channel with the rationale attached.

Where a human stays in control

  • A salesperson can override any score, and the override is recorded as training signal.
  • Nothing is ever replied to automatically — the agent qualifies, people respond.
  • Enquiries the agent is unsure about are routed for manual review rather than guessed.
  • Qualification criteria are yours in writing, and you change them without us.

Integrations

  • CRM

    Read and write deals, contacts and activities so qualified enquiries land where sales already works.

  • Telegram

    Bot-based notifications, approvals and conversational entry points for teams that already live there.

  • Google Workspace

    Sign-in, Drive, Sheets and Calendar as data sources and destinations for automated workflows.

  • REST API

    Documented, versioned and authenticated endpoints — both consuming yours and exposing ours.

Expected effect

Described qualitatively. Actual impact depends on your volumes, data quality and process discipline.

  • High-value enquiries reach an owner sooner, because ordering stops being purely chronological.
  • Sales spend less of their day triaging and more of it on conversations.
  • Marketing gets consistent, structured feedback on lead quality by source.
  • Duplicates and existing customers are caught before someone pitches them again.

Limits and what this does not do

  • It cannot judge fit better than your criteria describe it. Vague criteria produce vague scoring, and the first workshop is usually spent making them explicit.
  • It does not enrich from external data sources unless you license them separately.
  • Scoring on very low enquiry volumes is not worth automating — the tuning cost exceeds the benefit.

Part of the practice

AI Agents

Agents scoped to one workflow, integrated with your systems, always reviewable by a person.

Next use case

AI Customer Support

First-line answers grounded in your documentation, with citations and designed escalation.