InData Labs vs SoftKraft: full comparison for 2026
Quick verdict
InData Labs (3.9/5) edges ahead of SoftKraft (3.9/5) overall. InData Labs is the better choice for teams needing data science consulting before a generative AI build. SoftKraft is the stronger option for startups on tight budgets needing generative AI strategy advice. 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 | 3.9 / 5 | 3.9 / 5 |
| Primary differentiator | Data-science-first heritage predating the generative AI branding wave | Small dedicated team priced for startup 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. Staff estimates swing between roughly 65 and 200 across sources. Its practice centers on data science consulting, predictive analytics, natural language processing, and computer vision, positioning it closer to a data-first consultancy than a generative-AI-branded agency chasing the current trend.
SoftKraft
SoftKraft was founded in 2015 by CEO Marek Petrykowski and CTO Blazej Kosmowski, running a lean 11-50 person team from Bielsko-Biala, Poland. Around 70% of its clients are North American despite the delivery team sitting in Poland. The firm's positioning centers on data-driven software, generative AI consulting, and data engineering built specifically for startups and small-to-mid-sized companies, not enterprise accounts.
Services and capabilities: InData Labs vs SoftKraft
| Capability | InData Labs | SoftKraft |
|---|---|---|
| AI strategy consulting | ✓ | ✓ |
| Generative AI | ✗ | ✗ |
| Machine learning | ✓ | ✓ |
| Data engineering | ✓ | ✓ |
| MLOps | ✗ | ✗ |
| Fixed-price projects | ✓ | ✓ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: InData Labs vs SoftKraft
| Framework / platform | InData Labs | SoftKraft |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | N/A |
| LangChain | N/A | N/A |
| PyTorch | 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 | Getting a data science consulting assessment before committing to a full generative AI build., Adding computer vision strategy to a product that already produces image or video data. | Getting a generative AI strategy assessment for a pre-seed or seed-stage startup., Getting generative AI consulting and data engineering handled by one small, accountable team. |
| Typical project type | Fixed project | Fixed project |
InData Labs vs SoftKraft: pros and cons
| InData Labs | |
|---|---|
| + | Founder's gaming background brings real-time data processing experience to computer vision work. |
| + | Cyprus headquarters (EU-based) can simplify GDPR-aligned data handling for European clients. |
| + | Predictive analytics and NLP expertise predates the current generative AI wave. |
| + | More than a decade of track record in a narrower, more defensible specialty. |
| - | Reported team size varies close to 3x across public sources |
| - | Less generative AI and LLM-specific public case work than firms built specifically around that |
| SoftKraft | |
|---|---|
| + | Smaller team size keeps overhead, and likely cost, below mid-size and enterprise consultancies. |
| + | 70% North American client base shows the team has adapted to US buyer expectations from Poland. |
| + | Founder-led leadership stays close to delivery rather than purely sales. |
| + | Startup and SME focus means scope and pricing fit smaller budgets from the outset. |
| - | Team of 11-50 limits capacity to a handful of concurrent projects |
| - | Less public case-study history than firms with a decade-plus track record |
Who should choose InData Labs?
A typical fit: getting a data science consulting assessment before committing to a full generative AI build.
Data-science-first heritage predating the generative AI branding wave. Minimum engagement is not publicly disclosed. Works best with clients in Retail & e-commerce, Gaming, Fintech, Healthcare.
Who should choose SoftKraft?
A typical fit: getting a generative AI strategy assessment for a pre-seed or seed-stage startup.
Small dedicated team priced for startup 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 | InData Labs |
Use case fit: InData Labs vs SoftKraft
| Use case | InData Labs fit | SoftKraft fit | Winner |
|---|---|---|---|
| Getting a data science consulting assessment before committing to a full generative AI build. | Strong | Strong | Both equally |
| Adding computer vision strategy to a product that already produces image or video data. | Strong | Limited | InData Labs |
| Getting a generative AI strategy assessment for a pre-seed or seed-stage startup. | Strong | Strong | Both equally |
| Getting generative AI consulting and data engineering handled by one small, accountable team. | Strong | Strong | Both equally |
| Fixed-price project | Limited | Limited | Both equally |
| Dedicated team model | Limited | Limited | Both equally |
Verdict: InData Labs vs SoftKraft
InData Labs (3.9/5) is the stronger overall choice for most Generative AI Consulting projects. Data-science-first heritage predating the generative AI branding wave.
SoftKraft (3.9/5) is worth a look if you need getting generative AI consulting and data engineering handled by one small, accountable team. If your situation matches that, SoftKraft is a competitive option.
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InData Labs vs SoftKraft FAQ
Is InData Labs better than SoftKraft?
InData Labs (3.9/5) scores higher overall, but "better" depends on your use case. InData Labs's strongest advantage: Founder's gaming background brings real-time data processing experience to computer vision work. SoftKraft's strongest advantage: smaller team size keeps overhead, and likely cost, below mid-size and enterprise consultancies.
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 firm before shortlisting.
What are the main differences between InData Labs and SoftKraft?
InData Labs's primary differentiator is: data-science-first heritage predating the generative AI branding wave. SoftKraft's primary differentiator is: small dedicated team priced for startup 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 firm before making a decision.