CUSTOM AI AGENTS · Research & data
Data cleanup assistantas part of your team.
Detect duplicates. Normalize formats. Propose traceable corrections.
Explore this agent for my team ↗01 · THE WORK, STEP BY STEP
How the task moves forward.
Information helps when it can be checked. We define questions, periods and sources for analysis that explains both findings and limitations.
- 01
Detect duplicates
Identifies similar records and flags matches without deleting originals.
- 02
Normalize formats
Suggests consistent formats for dates, references and agreed fields.
- 03
Propose traceable corrections
Delivers reviewable differences with reasons and original values.
02 · ILLUSTRATIVE EXAMPLE
A situation that may feel familiar.
A business standardizes customer references while retaining original records.
Illustrative scenario, not a customer case study or measured results.
GmailExampleCapture the brief and its conditions.
NotionExampleDistinguish research coverage from verified amounts.
Research coverage
| Data item | Coverage |
|---|---|
| Competitors included in the brief | 5 |
| Located public price | 3 |
| Price without public source | 2 |
| Comparison | Offering, audience and terms |
NotionExampleKeep the references and distinguish confirmed data from pending items.
Competitor map · Review
Comparison criterion
Compare offering, audience and price under equivalent conditions. Keep each source reference.
Pending
Two competitors require an enquiry for pricing. Check dates and conditions before presenting conclusions to the client.
GmailExampleExplain the result and what is still pending.
03 · YOUR WAY OF WORKING
Fits the business you already have.
Context and tools
We start with your current documents, systems and channels. We assess feasible connections and define the permissions required for this specific task.
Improves with your feedback
Approved corrections are incorporated into instructions, examples or knowledge sources. We review changes before expanding the agent’s scope.
A clear way to evaluate
We agree on a representative sample and measure review time, errors, exceptions and output quality against the current workflow. Feasibility is decided using that evidence.
04 · COMMON QUESTIONS
Before getting started.
What information does this agent need?
Original tables and data quality rules. We review quality, currency and access before connecting the workflow. You do not need to replace all your tools to begin.
What will my team receive?
Reviewable changes and an issue log. We agree on the format and delivery channel during setup, together with cases that need review.
Which decisions remain with people?
Conclusions are reviewed in light of data quality, coverage and uncertainty.
Can it coordinate with other agents?
Yes. We define what this agent hands to the next one and who handles exceptions. It can interact through Slack, WhatsApp, email or Microsoft Teams, depending on the integration and permissions we configure.
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How would this fit your business?
Tell us how you do it today. We will define the scope, tools and controls with you.