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AI agent for technical support specialists

Support Attachment Interpretation Agent

A clear, evidence-based next diagnostic step for every ticket with attachments.

Support Attachment Interpretation Agent: what goes in, what the agent does and what you get

What it does

Tickets often arrive with screenshots, logs and descriptions that do not tell the same story. Agents then guess and ask generic questions. This agent reads every attachment, uses text recognition on screenshots, and places all events on one timeline. It forms a working hypothesis and lists where the sources disagree. It then runs one permitted diagnostic query that would settle the biggest disagreement and checks whether the result supports the hypothesis. If not, it revises the hypothesis, looks at the relevant timestamp again, and repeats. It ends with an evidence map and a specific next step on the ticket. The support agent approves any message to the customer. Edge case: when screenshot times and log times are in different time zones, it aligns them before comparing.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Ticket with attachments 2 USES A TOOL Read screenshots (OCR) and logs into one timeline 3 DOES Form a hypothesis and list disagreements 4 USES A TOOL Run a permitted diagnostic query 5 CHECKS THE RESULT Does the evidence support the hypothesis? If not: revise the hypothesis and inspect the relevanttimestamp. Back to step 3. 6 DOES Write the evidence map and next step 7 YOU APPROVE Agent approves any customer communication 8 RESULT Targeted investigation note on the ticket
Read the steps as a list
  1. Ticket with attachments
  2. Read screenshots (OCR) and logs into one timeline
  3. Form a hypothesis and list disagreements
  4. Run a permitted diagnostic query
  5. Does the evidence support the hypothesis?If not: revise the hypothesis and inspect the relevant timestamp. Back to step 3.
  6. Write the evidence map and next step
  7. Agent approves any customer communicationThe agent waits here for your OK.
  8. Targeted investigation note on the ticket

How it decides

It chooses queries to resolve disagreements between attachments; when a log contradicts its reading of a screenshot, it revises the hypothesis and inspects that timestamp.

  • Which query to run: the permitted one that resolves the biggest disagreement in the timeline.
  • Revise the hypothesis: when the query result or logs contradict the screenshot reading.
  • Time alignment: convert all sources to one time zone before judging order of events.
  • Stop and hand over: after three hypotheses without support, write the evidence map and ask a senior agent.

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Diagnostic queries the agent may run (default read-only account and session queries)
  • Maximum hypothesis rounds before handing over (default 3)
  • Attachment types read (default images, log files, HAR files)
  • Default time zone for the timeline (default UTC)
  • Who approves customer messages (default the assigned support agent)

What keeps you in control

It always asks you first

  • Customer communications
  • Production changes

Hard limits

  • Read-only.

It stops when

  • Done: hypothesis supported by evidence.
  • Needs a human: evidence insufficient.

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensA ticket from Copperline Retail on October 2 shows a 'payment failed' screenshot at 14:02. The log shows a failure at 13:02 UTC, before login. The agent's payment hypothesis fails the check. After aligning the time zones it sees the same event, revised as an authentication timeout. A permitted session query confirms it. Agent Rhea Patel approves a reply asking the customer to clear saved credentials.

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