InData Labs vs SoftKraft: full comparison for 2026
Quick verdict
InData Labs (4.1/5) edges ahead of SoftKraft (4.0/5) overall. InData Labs is the better choice for teams needing data science depth before an AI product build. SoftKraft is the stronger option for startups on a budget needing data-driven MVP work. The right choice depends on your project size, budget, and required tech stack.
InData Labs vs SoftKraft: head-to-head summary
| Criterion | InData Labs | SoftKraft |
|---|---|---|
| Founded | 2014 | 2015 |
| HQ | Limassol, Cyprus | Bielsko-Biala, Poland |
| Team size | 51-200 | 11-50 |
| Rating | 4.1 / 5 | 4.0 / 5 |
| Primary differentiator | Data-science-first practice rather than a generative-AI-branded service line | Small dedicated team pricing squarely at startup and SME budgets, not enterprise rates |
| Pricing model | Fixed project or dedicated team | Fixed project or dedicated team |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, scikit-learn, TensorFlow | Python, PostgreSQL, Apache Airflow |
| Industries served | Retail & e-commerce, Gaming, Fintech, Healthcare | Fintech, SaaS, Healthtech |
InData Labs vs SoftKraft: overview
InData Labs
InData Labs was founded in 2014 by gaming-industry veteran Marat Karpeko and is headquartered in Cyprus, with additional offices reported in Lithuania and the US. Employee figures vary from roughly 65 to 200 across different trackers, which is common for firms that mix core staff with project-based contractors. The company's practice centers on data science consulting: predictive analytics, natural language processing, computer vision, and big data analytics, positioned as a data-first alternative to firms that lead with generative AI branding.
SoftKraft
SoftKraft was founded in 2015 by CEO Marek Petrykowski and CTO Blazej Kosmowski, and is headquartered in Bielsko-Biala, Poland with roughly 11-50 staff. About 70% of its client base sits in North America, despite the delivery team being based in Poland, which reflects a common nearshore pattern for smaller AI consultancies. The firm specializes in custom data-driven software, AI, and data engineering aimed specifically at startups and small to mid-sized enterprises rather than large corporate accounts.
Services and capabilities: InData Labs vs SoftKraft
| Capability | InData Labs | SoftKraft |
|---|---|---|
| Generative AI | ✗ | ✗ |
| Machine learning | ✓ | ✓ |
| AI agents | ✗ | ✗ |
| MLOps | ✗ | ✗ |
| AI consulting | ✗ | ✓ |
| Fixed-price projects | ✓ | ✓ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: InData Labs vs SoftKraft
| Framework / platform | InData Labs | SoftKraft |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | N/A | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: InData Labs vs SoftKraft
| Criterion | InData Labs | SoftKraft |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed project, Dedicated team | Fixed project, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: InData Labs vs SoftKraft
| Dimension | InData Labs | SoftKraft |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Retail & e-commerce, Gaming, Fintech | Fintech, SaaS, Healthtech |
| Best use cases | Building predictive models from an existing data warehouse or event stream., Adding computer vision to a product that already generates image or video data. | Building a data-driven MVP for a pre-seed or seed-stage startup., Getting AI and data engineering from one small, accountable team instead of splitting the work. |
| Typical project type | Fixed project | Fixed project |
InData Labs vs SoftKraft: pros and cons
| InData Labs | |
|---|---|
| + | Founder's gaming-industry background brings real-time data experience to computer vision work. |
| + | EU-based headquarters (Cyprus) can simplify GDPR-aligned data handling for European clients. |
| + | Predictive analytics and NLP depth predate the generative AI hype cycle. |
| + | Decade-plus track record in a narrower, more defensible specialty than broad AI consulting. |
| - | Reported team size varies close to 3x across public sources |
| - | Less public-facing generative AI and LLM case work than firms built around that specifically |
| SoftKraft | |
|---|---|
| + | Small team size keeps overhead, and likely cost, lower than mid-size and enterprise firms on this list. |
| + | 70% North American client base shows the team has adapted to US buyer expectations despite being based in Poland. |
| + | Founder-led leadership stays close to delivery rather than purely sales. |
| + | Startup and SME focus means pricing and scope are built for smaller budgets from the start. |
| - | Team of 11-50 limits capacity for anything beyond a handful of concurrent projects |
| - | Less public case-study depth than firms with a decade-plus track record |
Who should choose InData Labs?
A typical fit: building predictive models from an existing data warehouse or event stream.
Data-science-first practice rather than a generative-AI-branded service line. Minimum engagement is not publicly disclosed. Works best with clients in Retail & e-commerce, Gaming, Fintech, Healthcare.
Who should choose SoftKraft?
A typical fit: building a data-driven MVP for a pre-seed or seed-stage startup.
Small dedicated team pricing squarely at startup and SME budgets, not enterprise rates. Minimum engagement is not publicly disclosed. Works best with clients in Fintech, SaaS, Healthtech.
Decision matrix: InData Labs vs SoftKraft
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | InData Labs |
| You need a large dedicated team for an ongoing programme | InData Labs |
| Your budget is at the lower end | Compare: InData Labs (Not disclosed) vs SoftKraft (Not disclosed) |
| You need specialist depth in a specific vertical | InData Labs |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | SoftKraft |
Use case fit: InData Labs vs SoftKraft
| Use case | InData Labs fit | SoftKraft fit | Winner |
|---|---|---|---|
| Building predictive models from an existing data warehouse or event stream. | Strong | Strong | Both equally |
| Adding computer vision to a product that already generates image or video data. | Strong | Limited | InData Labs |
| Building a data-driven MVP for a pre-seed or seed-stage startup. | Strong | Strong | Both equally |
| Getting AI and data engineering from one small, accountable team instead of splitting the work. | Limited | Strong | SoftKraft |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: InData Labs vs SoftKraft
InData Labs (4.1/5) is the stronger overall choice for most AI Development projects. Data-science-first practice rather than a generative-AI-branded service line.
SoftKraft (4.0/5) is worth a look if you need getting AI and data engineering from one small, accountable team instead of splitting the work. If your situation matches that, SoftKraft is a competitive option.
Related comparisons
InData Labs vs SoftKraft FAQ
Is InData Labs better than SoftKraft?
InData Labs (4.1/5) scores higher overall, but "better" depends on your use case. InData Labs's strongest advantage: Founder's gaming-industry background brings real-time data experience to computer vision work. SoftKraft's strongest advantage: small team size keeps overhead, and likely cost, lower than mid-size and enterprise firms on this list.
How do InData Labs and SoftKraft differ in pricing?
InData Labs uses fixed project or dedicated team pricing. SoftKraft uses fixed project or dedicated team pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: InData Labs or SoftKraft?
InData Labs 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 InData Labs and SoftKraft?
InData Labs's primary differentiator is: data-science-first practice rather than a generative-AI-branded service line. SoftKraft's primary differentiator is: small dedicated team pricing squarely at startup and SME budgets, not enterprise rates. They also differ in team size (51-200 vs 11-50), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Retail & e-commerce, Gaming vs Fintech, SaaS).
Verify all details directly with each company before making a decision.