Hakkoda vs Netguru: full comparison for 2026
Quick verdict
Hakkoda (3.9/5) edges ahead of Netguru (3.6/5) overall. Hakkoda is the better choice for buyers wanting IBM-backed stability for data-and-AI advisory work. Netguru is the stronger option for digital product companies wanting a proven internal-agent case study translated into advisory work. The right choice depends on your project size, budget, and required tech stack.
Hakkoda vs Netguru: head-to-head summary
| Criterion | Hakkoda | Netguru |
|---|---|---|
| Founded | 2021 | 2008 |
| HQ | New York, NY, USA | Poznań, Poland |
| Team size | 201-400 | 501-1000 |
| Rating | 3.9 / 5 | 3.6 / 5 |
| Best for | Buyers wanting IBM-backed stability for data-and-AI advisory work | Digital product companies wanting a proven internal-agent case study translated into advisory work |
| Pricing model | Retainer, fixed project | Dedicated team, retainer |
| Min. engagement | $35K | $25K |
| Primary tech stack | AWS, Azure, GCP | OpenAI, AWS, Node.js |
| Industries served | Fintech, Healthcare, Retail | SaaS, Fintech, Retail |
Hakkoda vs Netguru: overview
Hakkoda
Hakkoda was founded in 2021 and is headquartered in New York City, with 371 employees. The firm is a modern data consultancy helping companies harness cloud platforms and AI capabilities, and was acquired by IBM in April 2025 — now operating as Hakkōda, an IBM Company, which buyers should factor into long-term roadmap and pricing expectations.
Netguru
Netguru was founded in 2008 and is headquartered in Poznań, Poland, with 501-1,000 employees across offices including Warsaw, Kraków, Wrocław, Gdańsk, and Białystok. The company built Omega, an internal AI agent that automates tasks and guides sales reps through the sales process, and offers similar agent advisory and build services to enterprise and startup clients.
Services and capabilities: Hakkoda vs Netguru
| Capability | Hakkoda | Netguru |
|---|---|---|
| Enterprise automation | ✓ | ✗ |
| Agent orchestration | ✗ | ✗ |
| RAG & knowledge agents | ✓ | ✗ |
| Data & analytics agents | ✓ | ✗ |
| LLM integration | ✗ | ✗ |
| Workflow integration | ✗ | ✓ |
Tech stack comparison: Hakkoda vs Netguru
| Framework / platform | Hakkoda | Netguru |
|---|---|---|
| LangChain | N/A | N/A |
| LangGraph | N/A | N/A |
| AutoGen | N/A | N/A |
| LlamaIndex | N/A | N/A |
| OpenAI | ✓ | ✓ |
| Anthropic Claude | N/A | N/A |
| Pinecone | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Hakkoda vs Netguru
| Criterion | Hakkoda | Netguru |
|---|---|---|
| Minimum engagement | $35K | $25K |
| Engagement models | Retainer, Fixed project, Staff augmentation | Dedicated team, Retainer, Fixed project |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Hakkoda vs Netguru
| Dimension | Hakkoda | Netguru |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Fintech, Healthcare, Retail | SaaS, Fintech, Retail |
| Best use cases | Data-platform advisory for AI agents, Cloud-and-AI capability advisory | Sales process automation advisory, Customer support agent strategy |
| Typical project type | Retainer | Dedicated team |
Hakkoda vs Netguru: pros and cons
| Hakkoda | |
|---|---|
| + | IBM backing (since April 2025) adds financial stability and enterprise credibility |
| + | Data-platform-first advisory approach suits agents that need reliable data foundations |
| + | Internal AI agent (per Hakkoda Labs) demonstrates applied capability beyond advisory |
| - | 2025 acquisition by IBM changes ownership structure and may shift pricing/positioning over time |
| - | Post-acquisition integration into IBM's broader practice could affect team continuity |
| Netguru | |
|---|---|
| + | Internal production agent (Omega) demonstrates real operational agent use, not just advisory pitches |
| + | Established digital product consultancy since 2008 with strong startup/scaleup portfolio |
| + | Multiple Poland offices provide solid EU delivery coverage |
| - | Broader digital-product identity means AI agent advisory is one of several service lines |
| - | Internal agent case study (Omega) is sales-process-specific, less evidence in other advisory domains |
Who should choose Hakkoda?
Hakkoda is the right choice for buyers wanting IBM-backed stability for data-and-AI advisory work.
IBM acquisition (April 2025) adds enterprise backing and cross-sell into IBM's broader AI portfolio. Minimum engagement starts at $35K. Works best with clients in Fintech, Healthcare, Retail.
Who should choose Netguru?
Netguru is the right choice for digital product companies wanting a proven internal-agent case study translated into advisory work.
Publicly documented internal production agent (Omega) as proof of applied advisory-to-delivery capability. Minimum engagement starts at $25K. Works best with clients in SaaS, Fintech, Retail.
Decision matrix: Hakkoda vs Netguru
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Hakkoda |
| You need a large dedicated team for an ongoing programme | Netguru |
| Your budget is at the lower end | Netguru |
| You need specialist depth in a specific vertical | Hakkoda |
| 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: Hakkoda vs Netguru
| Use case | Hakkoda fit | Netguru fit | Winner |
|---|---|---|---|
| Data-platform advisory for AI agents | Strong | Limited | Hakkoda |
| Cloud-and-AI capability advisory | Strong | Limited | Hakkoda |
| Sales process automation advisory | Limited | Strong | Netguru |
| Customer support agent strategy | Limited | Strong | Netguru |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Hakkoda vs Netguru
Hakkoda (3.9/5) is the stronger overall choice for most AI Agent projects. IBM acquisition (April 2025) adds enterprise backing and cross-sell into IBM's broader AI portfolio. It is best for buyers wanting IBM-backed stability for data-and-AI advisory work.
Netguru (3.6/5) is the better choice when digital product companies wanting a proven internal-agent case study translated into advisory work. If your situation matches those criteria, Netguru is a competitive option.
Related comparisons
Hakkoda vs Netguru FAQ
Is Hakkoda better than Netguru?
Hakkoda (3.9/5) scores higher overall, but "better" depends on your use case. Hakkoda is better for buyers wanting IBM-backed stability for data-and-AI advisory work. Netguru is better for digital product companies wanting a proven internal-agent case study translated into advisory work.
How do Hakkoda and Netguru differ in pricing?
Hakkoda uses retainer, fixed project pricing with a minimum engagement of $35K. Netguru uses dedicated team, retainer pricing with a minimum engagement of $25K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Hakkoda or Netguru?
Netguru is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each consultancy before shortlisting.
What are the main differences between Hakkoda and Netguru?
Hakkoda's primary differentiator is: ibm acquisition (april 2025) adds enterprise backing and cross-sell into ibm's broader ai portfolio. Netguru's primary differentiator is: publicly documented internal production agent (omega) as proof of applied advisory-to-delivery capability. They also differ in team size (201-400 vs 501-1000), minimum engagement ($35K vs $25K), and primary industries served (Fintech, Healthcare vs SaaS, Fintech).