TThynkBloxAI

Use cases

Where AI agents earn their keep

The processes teams automate first sit in finance operations, customer support, sales operations, HR, recurring reporting, and document handling — high volume, rule-heavy, and slow because a person has to read something.

Each use case below states what the work looks like today, what it looks like once an agent runs it, and the measures we hold the pilot to. Those measures are agreed with you before the build and compared against your own baseline afterwards.

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01By business function

Six processes worth automating first

Finance, support, and reporting usually top the list: they run daily, the inputs are messy, and the time cost is easy to measure.

Finance ops

Invoicing and payables

Supplier invoices arrive as PDFs and email attachments in a dozen layouts. An agent reads each one, matches it to the purchase order and goods receipt, checks tax and GST fields, posts the clean matches, and puts mismatches in a review queue with the discrepancy highlighted.

Today
A clerk opens each invoice, finds the PO, retypes the lines, and chases mismatches by email.
With agents
Clean invoices post automatically; the team works only the exceptions, with the reason already identified.

What we measure

  • Invoices processed per hour
  • Match rate without human touch
  • Days to close payables

Customer support

Ticket triage and reply drafting

Incoming tickets are classified by intent and urgency, enriched with the customer's order and history, and answered with a grounded draft that cites the source article or record. Routine cases resolve without a human; the rest are routed with the context already attached.

Today
Agents read every ticket cold, search several systems, and rewrite the same answers daily.
With agents
Routine tickets are answered or pre-drafted; complex ones arrive with history and a suggested next step.

What we measure

  • First response time
  • Share of tickets auto-resolved
  • Reopen rate

Sales ops

CRM hygiene and follow-up

Leads are enriched and de-duplicated on entry, call notes are transcribed into the CRM against the right record, quotes are prepared from your approved price list, and deals that have gone quiet are surfaced with a suggested next action.

Today
Reps type notes after hours, duplicates accumulate, and pipeline reports are argued with rather than used.
With agents
The CRM reflects reality without manual entry, and follow-ups are prompted from the data.

What we measure

  • Records updated per rep per week
  • Duplicate rate
  • Time from enquiry to quote

HR

Hiring and onboarding

Applications are screened against the written role brief with the reasoning recorded, interviews are scheduled across calendars, offer paperwork is generated from approved templates, and the joining checklist is run across IT, payroll, and access requests.

Today
A coordinator screens CVs manually and chases six teams to get a new joiner set up.
With agents
Screening is consistent and documented, and onboarding tasks are raised automatically on day one.

What we measure

  • Time to first interview
  • Time to fully onboarded
  • Screening consistency

Reporting

Recurring reports and MIS

Numbers are pulled from your systems on a schedule, reconciled against each other, and assembled into the weekly or monthly pack with the commentary drafted. Every figure links back to the source row so a reviewer can check it in one click.

Today
An analyst spends two days a month copying figures between spreadsheets.
With agents
The pack is drafted on schedule and the analyst reviews and interprets rather than assembles.

What we measure

  • Hours to produce the pack
  • Restatements after issue
  • Reporting lag in days

Document ops

Contract and document handling

Structured data is extracted from contracts, purchase orders, and shipping documents arriving by email, validated against your master data, and written into the system of record. Anything failing validation is held with the failing field flagged.

Today
Documents are keyed in by hand, with errors surfacing weeks later in reconciliation.
With agents
Documents are captured on arrival and validated before they reach the ledger.

What we measure

  • Extraction accuracy
  • Keying hours removed
  • Downstream correction rate
02Choosing the first process

What makes a good first candidate

Four tests. A process that passes all four is usually live within eight weeks.

High volume

The process runs daily or hourly. Volume is what converts a small time saving per item into a number worth acting on.

Rule-heavy but messy

There are clear rules, but the input arrives as PDFs, emails, and free text — which is exactly where a script fails and an agent does not.

Slow because someone must read

The delay is a person opening a document and deciding. That reading step is the part an AI agent removes.

Measurable today

You can state the current hours, cycle time, or error rate. Without a baseline there is nothing to prove after go-live.

The audit ranks your candidates against these tests. See what the audit covers.

Your process

Send us the one that eats the most hours

Describe it in a sentence. We will tell you whether an agent can run it, what would need to be true first, and roughly what it would take.

Describe your processCall +919244500709