# Altar.io vs DareData

> Two top-rated AI Development agencies in Lisbon. 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/altar-io-vs-daredata
Generated: 2026-09-17 · Curated by Gabor Kiss · No paid placements — inclusion, score, and rank are never sold.

## Facts
| | Altar.io | DareData |
|---|---|---|
| Editorial score | 52.8/100 | 64/100 |
| Hourly rate | not published | €45-85/hr (directory-listed) |
| Team size | 10-49 | 50-249 |
| Location | Lisbon, Portugal | Lisbon, Portugal |
| Founded | 2015 | 2019 |
| Last reviewed | 2026-09-09 | 2026-09-03 |
| Services | AI Development, AI Consulting, Generative AI | AI Development, AI Consulting, Generative AI |
| Industries | FinTech, SaaS & B2B, E-commerce | Manufacturing, FinTech |

## Our take on Altar.io
Reviewed 2026-09-09 by Gabor Kiss against published evidence.

A product studio for funded startups, and the case studies measure the client rather than the work. The Apiax study reports that the fintech went on to raise more than eight million dollars, win startup awards and grow past 75 people across five offices. The Krepling study opens with $4.3 million raised and a five-star review score. Both are real outcomes and neither tells you what Altar built or how it performed.

The AI in the portfolio mostly belongs to the products rather than to the engagements. Apiax turns financial regulation into machine-readable rules served through an API; Krepling is a no-code commerce platform with AI generating design templates. Altar's role in each is product engineering around that idea.

What the library does give you is volume and names: twenty-six case studies, sixteen of them naming the client, across fintech, commerce and marketplaces.

Best for founders who want a product built and taken to a raise, and who will ask separately what the team has trained, evaluated and put into production.

### Key strengths
- Twenty-six published case studies with the client named on sixteen of them, which is unusual volume for a studio of this size
- The startup track record is checkable: Apiax raised more than eight million dollars and grew past 75 people after the engagement
- Consistent focus on regulated fintech and commerce products rather than a scatter of unrelated verticals

### Good to know
- The studies report the client's funding and awards rather than what Altar built or how it performed—ask for the technical scope and the engineering outcome
- Most of the AI belongs to the client's product; ask which models the team trained, evaluated or operated itself
- No rate and no headcount are published—confirm team size and cost before a fixed-scope build

## Our take on DareData
Reviewed 2026-09-03 by Gabor Kiss against published evidence.

The NOS work is the anchor: a GenOS-orchestrated invoice pipeline that now handles around 65% of roughly 20,000 supplier invoices a month end to end, matching them to SAP purchase orders and routing the ambiguous rest to a 20-person review team, plus UVA, a retrieval assistant over 15,000-plus documentation pages that operators rate at 87% answer accuracy on the 20% of calls where it is used.

Outside the telco, the Heineken routing engine (an OSRM duration matrix plus constraint optimization) reports €100k in fuel savings and 10% more locations visited per day, and the COFICAB cable-design platform runs surrogate models and an optimizer over 50,000-plus geometry and material combinations, with the engineers on each study named.

Two things to weigh: NOS acquired 20% of DareData, so the four NOS studies are partly work for a shareholder, and the COFICAB and UVA pages both label their outcomes as still under measurement, so the hard numbers sit mostly in the invoice and routing work.

The weaker fit is buyers who want a model-level technical narrative—the studies name integrations, volumes and team members, not the language models or evaluation setup behind GenOS.

### Key strengths
- Directory rates of €45–85/h against named enterprise production systems
- Engineering writing with substance: a nugget-based RAG evaluation piece drawn from production work (August 2026) and a LiteLLM supply-chain advisory, next to 18 published success stories
- Third-party signals: Clutch 100 fastest-growing 2023, Deloitte Fast 50 Portugal 2025, Google Cloud, Microsoft and NVIDIA partner badges, and 130-plus specialists reported in March 2026

### Good to know
- NOS holds a 20% stake in DareData and supplies four of the 18 published studies—ask for a speakable reference outside the NOS group
- The homepage claims 95% production deployments and €100M-plus value generated with nothing on the site behind either figure—ask how they are counted
- GenOS is the firm's own platform and sits under the invoice, legal and Greenvolt work—confirm licensing terms and what your team can operate if the engagement ends

## Which to choose
Choose Altar.io for:
- closer collaboration at a smaller team scale
- disclosed specialization in SaaS & B2B / E-commerce

Choose DareData for:
- larger team capacity for multi-stream or enterprise-scale programs
- disclosed specialization in Manufacturing
- a higher overall editorial score

## Questions buyers ask

### Which has more FinTech experience, Altar.io or DareData?
Both agencies show documented FinTech work. Altar.io has the broader industry stack overall, with disclosed experience in SaaS & B2B, E-commerce beyond their shared focus.

### Which scores higher overall, Altar.io or DareData?
DareData scores 64/100, 11.2 points higher than Altar.io at 52.8/100. See our methodology for how scores are calculated.

### Which is faster to engage, Altar.io or DareData?
Neither publishes lead times, so this is a read on team size rather than a measured answer. Altar.io runs the smaller team, which usually means fewer procurement gates and a shorter path to kickoff. DareData runs a larger one, which tends to mean more steps but more capacity to start parallel workstreams. Current kickoff availability is the number that actually decides it — ask both.

### When should I consider both Altar.io and DareData?
Consider running parallel discovery briefs with Altar.io and DareData 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