# Converteo vs Ekimetrics

> Comparing AI Consulting options: Paris vs London. Side by side: published rates, team size, service and industry coverage, and the curator's assessment of both — pairings are never sold.

Canonical page: https://www.aiagencies.eu/compare/converteo-vs-ekimetrics
Generated: 2026-09-17 · Curated by Gabor Kiss · No paid placements — inclusion, score, and rank are never sold.

## Facts
| | Converteo | Ekimetrics |
|---|---|---|
| Editorial score | 70.8/100 | 52.8/100 |
| Hourly rate | not published | not published |
| Team size | 250+ | 50-249 |
| Location | Paris, France | London, United Kingdom |
| Founded | — | 2006 |
| Last reviewed | 2026-08-05 | 2026-09-07 |
| Services | AI Consulting, AI Agents, AI Development, AI Marketing | AI Consulting, AI Marketing, Generative AI |
| Industries | E-commerce, Manufacturing | E-commerce, Manufacturing, FinTech |

## Our take on Converteo
Reviewed 2026-08-05 by Gabor Kiss against published evidence.

Sharlie, the voice agent behind Orange's Sosh brand, is the most completely documented build in this register, and the detail is the point.

Converteo committed to a voice-to-voice architecture in April 2024, before the model reached general availability, specifically to avoid a later migration off a speech-to-text pipeline—a decision that bought roughly one second of latency against three. Around thirty specialized agents hand off between themselves, escalate to a human, and act on Orange's catalog, billing and account systems rather than only answering. Validation was modeled on how call-center advisors are trained. Virtual clients replay conversations at volume against an LLM-as-a-judge scoring price accuracy and brand posture, and an AI-specific bug bounty ran with around forty white hackers before launch. It went to production on 16 March 2026 with a mechanism to stop it.

The rest of the library is a decade of measurement and pricing work with named clients: Carrefour, Leroy Merlin, L'Oréal, ENGIE, BUT, Picard, Arkema.

The caveat is that this depth is exceptional rather than typical—most of the other cases describe data and marketing engineering, not AI.

### Key strengths
- One engagement documented end to end, including the architecture decision, its latency cost, the evaluation rig and the kill switch—no other agency here publishes at that level
- Evaluation as a discipline rather than an afterthought: virtual clients, an LLM-as-a-judge scoring price accuracy and brand posture, and an AI bug bounty before exposure to customers
- Ten-plus named clients across retail, energy and industry, with the work described case by case rather than listed as logos

### Good to know
- Outside the voice-agent work, most published cases are data and marketing engineering—confirm which practice your engagement lands in
- No headcount, founding year or rates published; scale and price both have to be established in conversation

## Our take on Ekimetrics
Reviewed 2026-09-07 by Gabor Kiss against published evidence.

Ekimetrics has 20 years of marketing-mix modeling behind it and 13 named clients on the site—Nestlé, Estée Lauder, Renault, Groupe SEB and Blablacar among them—but the named clients and the published case studies are not the same set.

The two most detailed cases are anonymous: a climate-risk engine consolidating more than 200 data points per assessment across 1,023 ISIC-coded industries using LLM-generated vulnerability assessments with expert validation, and a beauty-sector formulation system built to take a manufacturer from 50 to 500 approved formulas a year against a reformulation deadline covering 1,500+ products.

Both describe real method—the climate work anchors physical risk scoring in the INFORM Risk Index, the formulation work pairs Design of Experiments with the models—but neither says whose problem it solved.

The headline claim of $10 billion in gains delivered has no working shown, so treat the cases as the evidence and the aggregate as marketing.

### Key strengths
- Twenty years of marketing-mix modeling, with a Google Measurement Partner listing and a Microsoft solutions-partner designation in AI and Machine Learning
- The climate-risk work publishes its method: INFORM Risk Index for physical risk scoring, ISIC-compliant classification across 1,023 industries, expert validation before deployment
- Named clients span consumer, automotive and industrial brands—Nestlé, Estée Lauder, Renault, Groupe SEB

### Good to know
- The named clients and the published case studies are different sets—ask for a case study with the client's name on it
- The "$10B gains delivered and measured" figure is an aggregate with no methodology attached—ask how it is calculated
- The head office is Paris and London is one office—ask where your team sits and who leads the engagement

## Which to choose
Choose Converteo for:
- larger team capacity for multi-stream or enterprise-scale programs
- broader service offering — also covers AI Agents and AI Development
- a higher overall editorial score

Choose Ekimetrics for:
- closer collaboration at a smaller team scale
- disclosed specialization in FinTech
- broader service offering — also covers Generative AI

## Questions buyers ask

### Which has more E-commerce experience, Converteo or Ekimetrics?
Both agencies show documented E-commerce work. Ekimetrics has the broader industry stack overall, with disclosed experience in FinTech beyond their shared focus.

### Which scores higher overall, Converteo or Ekimetrics?
Converteo scores 70.8/100, 18 points higher than Ekimetrics at 52.8/100. Both portfolio quality and business credibility feed into the score — see our methodology for the full breakdown.

### When should I consider both Converteo and Ekimetrics?
Consider running parallel discovery briefs with Converteo and Ekimetrics if your project spans multiple workstreams, you want competitive proposals to compare scope and approach, or you're undecided between the specialization angles each brings (see the Best for cards above). Most engagements ultimately go with one — but the parallel-brief phase is a low-cost way to validate fit.

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Source: AIAgencies.eu — the curated register of European AI agencies. Rate provenance: "agency-confirmed" = disclosed via submission or claimed profile; "directory-listed" = Clutch or two agreeing B2B directories (lone unverified sources are never written). Full method: https://www.aiagencies.eu/methodology · Rate index: https://www.aiagencies.eu/rates