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Sales automation that gets leads to the right person while they are still interested.
THE BUSINESS PROBLEM
Sales teams lose time between systems: copying enquiries into the CRM, researching companies, chasing follow-ups and updating records after calls.
Common manual workflows
- Copying form and inbox leads into the CRMdaily
- Researching company size and fitper lead
- Deciding who owns a leadper lead
- Logging call notes and next stepsper call
What can be automated
- Capture leads from every form and inbox into one flow
- Deduplicate against existing contacts
- Enrich and score against your ideal customer profile
- Assign by territory and enrol in the right sequence
- Summarise calls into CRM fields
Example architecture
01 · TRIGGER
Forms + inbox
02 · ACTION
Validate + dedupe
03 · ACTION
Enrich
04 · DECISION
Fit score
05 · HUMAN
Review low-fit
06 · APP
CRM + sequence
Leads below the fit threshold go to a quick human review instead of being discarded.
Where humans remain involved
- Reviewing low-fit or unusual leads
- Approving outbound messaging templates
- Pricing and contract decisions
Example outcomes
- <1 min
- form to owner
- 0
- leads re-keyed
- 16h
- per week returned
Operations automation for the requests, approvals and handoffs that keep a business running.
THE BUSINESS PROBLEM
Operational work runs on forms, email and spreadsheets. Requests wait for someone to notice them, approvals stall, and status lives in people’s heads.
Common manual workflows
- Routing requests to the right teamdaily
- Chasing approvalsweekly
- Onboarding new staff across toolsper hire
- Compiling weekly status reportsweekly
What can be automated
- Intake from forms with validation
- Approval routing with reminders and escalation
- Task creation across project tools
- Onboarding: accounts, hardware requests, first-week tasks
- Scheduled reports from live data
Example architecture
01 · TRIGGER
Request form
02 · DECISION
Route by type
03 · HUMAN
Approver
04 · ACTION
Create tasks
05 · APP
Notify team
06 · DATA
Reporting
Approvals are routed by type and amount; the system handles reminders and records every decision.
Where humans remain involved
- Approving spend and access
- Handling requests outside the standard types
- Setting priorities between teams
Example outcomes
- 0
- requests lost in inboxes
- Same day
- approval turnaround
- 100%
- decisions logged
Finance automation with controls built in, not bolted on.
THE BUSINESS PROBLEM
Finance teams spend days on extraction, matching and reporting. The work is repetitive but the cost of error is high, so it stays manual.
Common manual workflows
- Keying invoices into accountingdaily
- Matching bank lines to invoicesweekly
- Analysing bank statementsmonthly
- Building management reportsmonthly
What can be automated
- Invoice and receipt extraction with validation
- Bank-to-ledger reconciliation
- Bank statement analysis: categorisation, anomaly flags, cash-flow summaries
- Approval routing by amount and cost centre
- Scheduled reports with commentary drafts
Example architecture
01 · TRIGGER
Statement / invoice
02 · ACTION
Extract
03 · DECISION
Reconciles?
04 · HUMAN
Analyst review
05 · APP
Accounting
06 · DATA
Reports
Anything that does not reconcile, or exceeds an amount threshold, waits for a named approver.
Where humans remain involved
- Approving payments and journal entries
- Reviewing flagged transactions
- Signing off reports before they are shared
Example outcomes
- 87%
- less processing time
- 0
- figures re-keyed
- Every
- approval auditable
Support automation that makes agents faster without speaking for them.
THE BUSINESS PROBLEM
Agents spend the first minutes of every ticket working out what it is about and looking up the customer across several tools.
Common manual workflows
- Tagging and routing ticketsper ticket
- Looking up orders and accountsper ticket
- Writing repeat answersdaily
- Escalating to the right teamdaily
What can be automated
- Classify intent and urgency on arrival
- Attach order and account context
- Draft replies from your knowledge base
- Escalate by rule with full context
- Report on gaps in documentation
Example architecture
01 · TRIGGER
New ticket
02 · ACTION
Classify
03 · DATA
Fetch context
04 · ACTION
Draft reply
05 · HUMAN
Agent sends
06 · APP
Help desk
Drafts are never sent automatically. Agents edit and send; edit rates are tracked per category.
Where humans remain involved
- Sending every customer-facing reply
- Refunds and account changes
- Complaints and sensitive cases
Example outcomes
- 52%
- faster first response
- 0
- unreviewed replies
- 2–3
- lookups removed per ticket
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