Case Studies — Elanova AI

Document Automation · Logistics

From 40 Hours of Data Entry to Zero

Three people manually keying 10,000+ invoices a month into the ERP. 40 hours of work per week, a 12% error rate, and a backlog that grew faster than the team could clear it. Two automation attempts had already failed. If that sounds like your data entry situation, keep reading.

10,000+ invoices now flow through the pipeline every month — read, classified, and routed automatically. Accuracy at 99%. Manual processing down 85%. The three people who used to do this work are now focused on vendor negotiations instead of spreadsheets.

Before

Manual entry → Spreadsheet → Email routing → 3 days / 12% errors

After

Invoice in → AI classify & extract → Auto-route to ERP → Minutes / 99% accuracy

Annual savings€155K

Error rate12% → <1%

3 FTEs redirected to higher-value work (est. €135K loaded salary) + error remediation and rework costs eliminated (est. €20K/yr).

AI Agents · SaaS

5,000 Conversations a Day — Without Hiring

5,000 support tickets a day. Two senior agents lost to burnout. Response times averaging 8 hours. A flagship enterprise client already asking questions about the SLA. The queue wasn’t a support problem — it was a business risk.

78% of those 5,000 daily conversations are now resolved automatically — the right answer pulled from a live knowledge base, delivered without a human in the loop. Complex cases still escalate to the team. The difference is the team now chooses which problems deserve their time, instead of drowning in volume.

Before

Email inbox → Manual triage → Agent reply → 8h avg response

After

Message in → AI agent + KB lookup → Auto-resolve or escalate → <2 min response

Annual savings€210K

Auto-resolved78% of tickets

Avoided hiring 5 additional support agents to handle volume growth. At ~€42K loaded cost per seat: 5 × €42K = €210K/yr in headcount not added.

Process Automation · Enterprise

The Workflow Engine That Replaced 6 Spreadsheets

Six spreadsheets, three email chains, and approval decisions that took days — sometimes longer. Every stakeholder waited on someone else. When anything slipped through the cracks, nobody could trace where.

Everything now moves through one platform. Requests are routed intelligently, approvals happen automatically where rules allow, and every item in the queue has a visible status in real time. Approvals that used to take days happen the same day. The team spends less time chasing and more time deciding.

Before

6 spreadsheets → 3 email chains → Manual approval → Days of lag

After

Request in → Smart routing → Auto-approvals → Live tracking

Annual savings€105K

Approval cycleDays → same-day

6 team members reclaiming ~2h/day previously spent on manual routing and approval chasing. 6 × 2h × 250 days × €35/h (fully loaded) = €105K.

Web Application · Analytics

Ask Your Data a Question. Get an Answer.

A question goes into Slack at 9am. Someone pings the data team. A SQL query gets written. A report lands the next morning. By then, the decision has already been made without the data — or delayed waiting for it. Sound familiar?

Type a question in plain English. The answer — complete with visualisation — appears instantly. No SQL, no data team bottleneck, no next-day wait. Business stakeholders get the numbers they need in the moment they need them, and the data team gets their time back.

Before

Business question → Slack data team → SQL query written → Report next day

After

Type question → AI → SQL → Auto-visualise → Instant answer

Annual savings€78K

Query timeNext-day → instant

Recurring BI contractor reports eliminated (€39K/yr) + 12h/week of senior analyst time freed at €31/h × 50 weeks (€39K).

Website · Local Business

A Phone Repair Shop That Looks Like It Belongs in 2026

No website. A Google Maps listing, and nothing else. Every potential customer who searched, found nothing credible, and moved on was a lost walk-in — invisible by default in a market where trust is decided in 10 seconds on a phone screen.

caremyphone.de now answers every question a potential customer has before they even call — services, pricing, repair process, real Google reviews. Bilingual copy, mobile-first design, 98/100 PageSpeed score. Built in 3 weeks. Every section is engineered to turn a search into a walk-in.

Before

No web presence → Word of mouth only → Zero online trust signals

After

Google search → Fast bilingual site → Walk-ins & bookings

PageSpeed score98 / 100

Launch time3 weeks

Document Automation · Healthcare

From 3-Day Backlog to Same-Day Patient Intake

Receptionists spending hours every day transcribing paper forms, field by field, into the EHR. Errors creeping into patient records. Paper files scattered across the clinic — a GDPR exposure that hadn’t been properly audited in months. If your intake process still involves manual data entry, the compounding risk is real.

Intake forms — handwritten or digital — now feed directly into the EHR the same day, with 97%+ extraction accuracy and zero manual transcription. Each form is validated before it syncs via HL7 FHIR API and immediately archived in an encrypted, GDPR-compliant store. The 3-day backlog is gone. So is the compliance exposure.

Before

Paper form → Manual transcription → EHR data entry → 3-day backlog

After

Scan / upload → AI extraction + validation → FHIR API sync → Same day / 97% accuracy

Annual savings€175K

Intake backlog3 days → same-day

~7.5 FTE-hours/day of transcription eliminated across the clinic network (€47K) + reduced GDPR exposure (€40K risk premium) + same-day processing unlocks patient throughput gains (€88K).

Process Automation · Finance

Month-End Close in 4 Days, Not 12

12 working days every month, four analysts, hundreds of manual reconciliation steps — and a 30% rework rate because entries didn’t match first time. Every close cycle was the same fire drill. If month-end means an all-hands scramble at your firm, you’ll recognise this.

Month-end close now takes 4 days. Transaction feeds are ingested, matched across accounts, and exceptions flagged automatically. Audit-ready reports generate on schedule, consistently formatted every time. The analysts still do the work that requires a human — reviewing edge cases — not the work a machine does better.

Before

Raw feeds → Manual matching → 30% rework → 12-day close

After

Transaction feeds → AI reconciliation engine → Exception queue → 4-day close / 99% accuracy

Annual savings€175K

Close cycle12 days → 4 days

4 analysts × 8 working days recovered per monthly close × 12 months × €365/day = €140K direct labor + restatement and rework costs eliminated (est. €35K).

AI Agents · E-commerce

800 Returns a Week. Handled in 6 Hours, Not 4 Days.

800+ returns every week, processed by hand — customer emails, product photos, reason codes, policy checks. Four people overwhelmed, decisions inconsistent depending on who picked up the ticket, and customers waiting 4 days for a refund answer. Every day of that wait is a customer who won’t buy again.

Returns are now processed in 6 hours. Every request is read, product photos analysed, and the policy applied consistently — full refund, partial, or reject with a clear explanation. Only genuine edge cases reach a human. The team went from 4 people firefighting returns to 1 person managing exceptions.

Before

Customer email + photos → Manual policy check → Human decision → 4-day SLA

After

Return request → AI classify + vision check → Auto-decision → 6h SLA

Annual savings€155K

Decision SLA4 days → 6h

Returns team reduced from 4 FTEs to 1 (3 × €38K = €114K saved) + consistent policy enforcement cuts fraud and chargeback losses (est. €41K/yr).

Document Automation · Manufacturing

ISO Audit Prep: From 6 Weeks to 3 Days

40+ production lines, and every ISO audit cycle meant 6 weeks of analyst time — pulling records, compiling reports, cross-referencing specs, hunting for gaps. Documentation never stayed current between cycles, so every audit started from scratch. The compliance burden wasn’t just expensive; it was unsustainable.

Production data now feeds into the compliance system continuously. ISO-formatted reports generate on a defined schedule. A tamper-evident change log maintains itself. Documentation gaps get flagged before the auditors find them. The next audit cycle took 3 days to prepare — not 6 weeks. Zero findings related to documentation completeness.

Before

Production records → Manual compilation → Gap hunting → 6-week audit prep

After

Live production data → Auto ISO report gen → Proactive gap alerts → 3-day audit prep

Annual savings€130K

Audit prep6 weeks → 3 days

4 analysts × ~48 weeks of audit prep reclaimed at €1,100/wk = €53K + external ISO consultancy eliminated (€65K) + avoided non-conformance penalties (€12K).

Work That Ships.Results That Hold.

From 40 Hours of Data Entry to Zero

5,000 Conversations a Day — Without Hiring

The Workflow Engine That Replaced 6 Spreadsheets

Ask Your Data a Question. Get an Answer.

A Phone Repair Shop That Looks Like It Belongs in 2026

From 3-Day Backlog to Same-Day Patient Intake

Month-End Close in 4 Days, Not 12

800 Returns a Week. Handled in 6 Hours, Not 4 Days.

ISO Audit Prep: From 6 Weeks to 3 Days

Work That Ships.
Results That Hold.