Best Generative AI Development Services

Softermii vs DataArt: full comparison for 2026

Quick verdict

Softermii (4.0/5) edges ahead of DataArt (3.9/5) overall. Softermii is the better choice for teams needing generative AI features inside a broader product build. DataArt is the stronger option for enterprises in finance or healthcare needing generative AI at global scale. The right choice depends on your project size, budget, and required tech stack.

Softermii vs DataArt: head-to-head summary

Criterion Softermii DataArt
Founded 2014 1997
HQ Los Angeles, United States New York, United States
Team size 51-120 5,700+
Rating 4.0 / 5 3.9 / 5
Primary differentiator Full-stack product development capability layered with newer generative AI service lines Nearly 30 years of engineering history across 30-plus global delivery locations
Pricing model Fixed project or dedicated team Dedicated team or retainer
Min. engagement Not disclosed Not disclosed
Primary tech stack Python, OpenAI API, React Python, OpenAI API, AWS
Industries served Healthcare, Fintech, Media & entertainment Financial services, Healthcare, Media & entertainment, Travel & hospitality

Softermii vs DataArt: overview

Softermii

Softermii has run out of Los Angeles since 2014, with reported staff between roughly 88 and 120 depending on source and date. Its core identity is custom software and platform development; generative AI is a newer, growing line rather than the founding specialty. Clients get a partner that builds the full surrounding product, not just a generative AI component, at the cost of the depth a dedicated AI-only agency can offer.

DataArt

DataArt goes back to 1997, founded by Eugene Goland, and is headquartered in New York City with roughly 5,700 employees spread across more than 30 locations. The firm delivers data, analytics, and generative AI platforms for finance, media and entertainment, healthcare, retail, and travel and hospitality clients. Nearly three decades of history gives it a longer track record than almost every other firm here, though generative AI is delivered as part of a broader software engineering practice rather than a standalone specialty.

Services and capabilities: Softermii vs DataArt

Capability Softermii DataArt
Generative AI
Machine learning
AI agents
MLOps
AI consulting
Fixed-price projects
Dedicated team model

Tech stack comparison: Softermii vs DataArt

Framework / platform Softermii DataArt
Python
OpenAI API
PyTorch N/A N/A
LangChain N/A N/A
AWS
Azure N/A
Kubernetes N/A N/A

Pricing comparison: Softermii vs DataArt

Criterion Softermii DataArt
Minimum engagement Not disclosed Not disclosed
Engagement models Fixed project, Dedicated team Dedicated team, Retainer
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: Softermii vs DataArt

Dimension Softermii DataArt
Best company size Startup to mid-market Startup to mid-market
Best industries Healthcare, Fintech, Media & entertainment Financial services, Healthcare, Media & entertainment
Best use cases Adding a generative AI feature to an existing web or mobile product., Building a new product where generative AI is one component among several. Building generative AI-driven analytics platforms for finance or healthcare clients., Running a long-term generative AI and data engineering program with a financially established vendor.
Typical project type Fixed project Dedicated team

Softermii vs DataArt: pros and cons

Softermii
+ Full-stack development means generative AI features ship inside a complete working product.
+ Over a decade of US-based software delivery experience.
+ Comfortable across web, mobile, and backend work, not just the AI layer.
+ Mid-size team keeps senior engineers directly involved on most projects.
- Generative AI is a newer service addition rather than a founding specialty
- Employee counts differ by roughly 35% across public trackers
DataArt
+ Nearly three decades of software engineering history, among the longest reviewed here.
+ 5,700-plus employees across 30-plus locations globally.
+ Named industry focus areas (finance, healthcare, travel) show real vertical depth.
+ Data and analytics platform experience supports generative AI work that needs solid data foundations.
- Generative AI sits inside a much broader software engineering practice rather than being the firm's core identity
- Enterprise scale typically means slower onboarding than smaller, more agile AI boutiques

Who should choose Softermii?

A typical fit: adding a generative AI feature to an existing web or mobile product.

Full-stack product development capability layered with newer generative AI service lines. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Fintech, Media & entertainment.

Who should choose DataArt?

A typical fit: building generative AI-driven analytics platforms for finance or healthcare clients.

Nearly 30 years of engineering history across 30-plus global delivery locations. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Media & entertainment, Travel & hospitality.

Decision matrix: Softermii vs DataArt

Your situation Recommended choice
You need full-ownership delivery on a defined project scope Softermii
You need a large dedicated team for an ongoing programme Softermii
Your budget is at the lower end Compare: Softermii (Not disclosed) vs DataArt (Not disclosed)
You need specialist depth in a specific vertical DataArt
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
You need consulting before committing to a build Both may offer discovery engagements

Use case fit: Softermii vs DataArt

Use case Softermii fit DataArt fit Winner
Adding a generative AI feature to an existing web or mobile product. Strong Limited Softermii
Building a new product where generative AI is one component among several. Strong Strong Both equally
Building generative AI-driven analytics platforms for finance or healthcare clients. Strong Strong Both equally
Running a long-term generative AI and data engineering program with a financially established vendor. Limited Strong DataArt
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: Softermii vs DataArt

Softermii (4.0/5) is the stronger overall choice for most Generative AI Development projects. Full-stack product development capability layered with newer generative AI service lines.

DataArt (3.9/5) is worth a look if you need running a long-term generative AI and data engineering program with a financially established vendor. If your situation matches that, DataArt is a competitive option.

Related comparisons

Softermii vs DataArt FAQ

Is Softermii better than DataArt?

Softermii (4.0/5) scores higher overall, but "better" depends on your use case. Softermii's strongest advantage: full-stack development means generative AI features ship inside a complete working product. DataArt's strongest advantage: nearly three decades of software engineering history, among the longest reviewed here.

How do Softermii and DataArt differ in pricing?

Softermii uses fixed project or dedicated team pricing. DataArt uses dedicated team or retainer pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: Softermii or DataArt?

Softermii is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.

What are the main differences between Softermii and DataArt?

Softermii's primary differentiator is: full-stack product development capability layered with newer generative AI service lines. DataArt's primary differentiator is: nearly 30 years of engineering history across 30-plus global delivery locations. They also differ in team size (51-120 vs 5,700+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Healthcare, Fintech vs Financial services, Healthcare).

Verify all details directly with each company before making a decision.