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AI agents & workflow automation

Turn messy business operations into clean AI workflows.

We build custom AI agents, data collection systems, dashboards and automated reporting for business teams in manufacturing, industrial service and B2B sales. You start with one focused pilot.

Book a Discovery CallSee how it works

TodaySpread across Excel, Slack, Outlook, texts and hand-typed reports.

ExcelInstalled_base_v7_FINAL(2).xlsx
SlackMike: Unit 3 pressure running high, heading on site tomorrow
OutlookRE: RE: Q3 dealer equipment list
Paper reportService_report_Midwest_scan.pdf
Text messageSarah: customer wants to renew, who's on it?
ERP exporterp_export.csv: SN-40317 listed 3 times

With RootCleanOne structured, reviewed record.

AssetUpdateOwnerStatus
Installed base register3 versions mergedData teamValidated
Unit 3, Site APressure high, visit bookedMike, fieldScheduled
Dealer Q3 listSubmitted for reviewDealer EastIn review
Midwest service reportBuilt from field dataRegional mgrApproved
Customer renewalFlagged as opportunitySalesOpportunity
SN-40317Duplicates resolvedSystemValidated

Sample records. Your fields, roles and rules are set up during the pilot.

The problem

Your data is not missing. It is scattered.

The information already exists, across spreadsheets, chats and inboxes. What is missing is one clean, governed place for it to live.

  • Spreadsheets nobody owns

    Every team keeps its own version. Field definitions drift, totals never reconcile, and someone re-keys the same numbers every month.

  • Field updates stuck in chat

    What engineers and dealers learn on site lives in WeChat threads. It never reaches a system, so managers can't see the service and sales opportunities in it.

  • AI pilots that stall

    The model is rarely the bottleneck. The workflow underneath isn't ready, so pilots never reach real operations.

How it works

How a workflow gets clean

Five steps, each one something your team can see and check.

  1. 01Field collection

    Sales, dealers and engineers submit through one simple form, on phone or desktop.

  2. 02Structured store

    Every submission lands in one database with the same fields and definitions.

  3. 03Rule validation

    Duplicates, missing fields and out-of-range values are flagged automatically.

  4. 04Review and approval

    The right person checks and signs off before anything is reported.

  5. 05Dashboard

    Managers see live status, reports and opportunities without asking for a spreadsheet.

What RootClean AI builds

Four building blocks, adopted one at a time

Start with the one that hurts most. Add the next when the first is working.

01

Business data collection system

For field sales, dealers, engineers and service teams

Replace emailed spreadsheets with forms that check data as it's entered.

02

AI workflow automation

For operations and approval-heavy teams

AI agents take over the repetitive Excel, reporting and approval steps between people.

03

Dashboard and reporting

For managers and leadership

Turn operational data into live views and monthly reports that build themselves.

04

Market intelligence agent

For strategy, sales and business development

An agent collects, analyzes and summarizes industry signals, and a person reviews each one.

Case study

Three AI agents for one global industrial equipment company

Each agent took over one team’s manual work: management reporting, tender follow-up, equipment inspection. The parts all three share are now reusable RootClean modules, and your pilot starts from them.

01Service · Installed baseIn use

Natural-language dashboard agent

Managers ask a question in plain words and get a dashboard back. Every figure is computed from live field records, limited to what that manager may see.

Ask your dataSample data
Which units are due for service in the next 3 months?

Analysis picked: upcoming maintenance · 412 records

37Units due
12Customers
Nov
Dec
Jan

Most units fall due in December, 9 of them for a major overhaul.

What changed

300 hrsOf manual reporting removed each month
1,600+Service opportunities surfaced in the first three months
02Sales · Public tendersIn use

Lead ranking and routing agent

Every new tender notice is screened, ranked by deal size and sent to the salesperson who manages that customer, with the reason logged.

Incoming tendersSample data
  1. 3Food plant · separator overhaul¥310k · 6 installed unitsNormalEast region rule
  2. –Steel mill · new pump purchase¥5.2M · equipment onlyExcluded: equipment purchase
  3. 2Chemical plant · gasket replacement¥860k · 34 installed unitsHighJ. Chen, account manager
  4. 1District heating · plate cleaning¥2.4M · 62 installed unitsHighL. Wang, account manager

What changed

39,590Real tender notices run through the screening rules
9,933Award notices now used for lost-deal analysis
03Field service · Thermal inspectionPrototype

Predictive thermal inspection agent

The agent compares each thermal scan with the unit’s history, spots fouling before efficiency drops and recommends the next step for an engineer to confirm.

Unit E-101 · plate heat exchangerIllustrative
MarHealth 92
JunHealth 78
SepHealth 61

Cold zone at the inlet, larger in every scan

Fouling risk: high

Backflush within 4 weeks

Cold zone grew in 3 scans in a row; cold-side outlet 3.1 °C below a similar unit

Engineer to confirm

What changed

32Thermal images from 4 real service reports, used to define the workflow
4 stagesFrom screening single images to per-unit prediction, each stage unlocked by data

What carries over to your pilot

  • Rules first, AI for the judgment calls

    Your rulebook answers the look-up questions. The agent takes only what needs judgment, so results stay consistent.

  • Every result shows its source

    Figures come from your records, exclusions cite the rule, findings cite the evidence.

  • Matched to your master data

    Free-text customer names and equipment IDs are resolved against your CRM and installed base. Confirmed matches are remembered.

  • Configured, not rebuilt

    Adding a product line, business unit or rule is configuration work, not a new project.

Client name shared on request. Figures come from the client’s own systems and reports. The animations use sample data.

Use cases

Built for traditional enterprises

We work with business departments, not just IT, in manufacturing, industrial service, F&B and B2B sales.

  • Industrial service

    Installed base records, service visits and field reports in one flow.

  • Dealer data collection

    Dealers submit to one standard, and sales reviews before it counts.

  • Sales operations

    Customer and pipeline updates captured from the field, not chased in chat.

  • Management reporting

    Monthly packs built from live data instead of copied spreadsheets.

  • Market intelligence

    An agent gathers and summarizes industry signals for review.

  • Excel and PPT automation

    Recurring workbooks and decks generated from the same source.

Data ownership

Your data stays yours

  • You own the data

    Business data belongs to you. The framework underneath is RootClean's reusable capability.

  • Role-based access

    Each role sees and edits only what it should.

  • People approve

    Nothing is reported until the right person has reviewed it.

  • Export any time

    Reports and records export to the formats your team already uses.

Next step

Show us the spreadsheet your team dreads every month.

In a 30-minute call we map where the data comes from, who touches it, and what a pilot would clean up first.

Book a Discovery Callbill@rootcleanai.com