KPMG vs SoftKraft: full comparison for 2026
Quick verdict
KPMG (4.1/5) edges ahead of SoftKraft (3.9/5) overall. KPMG is the better choice for enterprises wanting productized AI tools alongside Big Four consulting. SoftKraft is the stronger option for startups on tight budgets needing AI strategy advice. The right choice depends on your project size, budget, and required tech stack.
KPMG vs SoftKraft: head-to-head summary
| Criterion | KPMG | SoftKraft |
|---|---|---|
| Founded | 1987 | 2015 |
| HQ | London, United Kingdom | Bielsko-Biala, Poland |
| Team size | 251,000-275,000 | 11-50 |
| Rating | 4.1 / 5 | 3.9 / 5 |
| Primary differentiator | Named AI products (aIQ, Mystro) rather than purely bespoke consulting engagements | Small dedicated team priced for startup budgets, not enterprise rates |
| Pricing model | Retainer, enterprise contracting | Fixed project or dedicated team |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, AWS, Azure | Python, PostgreSQL, Apache Airflow |
| Industries served | Financial services, Healthcare, Manufacturing, Government | Fintech, SaaS, Healthtech |
KPMG vs SoftKraft: overview
KPMG
KPMG formed in 1987 from the merger of Peat Marwick International and Klynveld Main Goerdeler, with roots tracing back to 1897, and is headquartered in London. The firm employs roughly 251,875-275,288 people depending on the reporting period. Its AI services include named products such as aIQ and Mystro for AI transformation and digital labor optimization, giving it more named AI products than some Big Four peers, though details on team size specifically dedicated to AI weren't disclosed.
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, AI consulting, and data engineering built specifically for startups and small-to-mid-sized companies, not enterprise accounts.
Services and capabilities: KPMG vs SoftKraft
| Capability | KPMG | SoftKraft |
|---|---|---|
| AI strategy consulting | ✓ | ✓ |
| Generative AI | ✗ | ✗ |
| Machine learning | ✓ | ✓ |
| Data engineering | ✗ | ✓ |
| MLOps | ✗ | ✗ |
| Fixed-price projects | ✗ | ✓ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: KPMG vs SoftKraft
| Framework / platform | KPMG | SoftKraft |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | ✓ | N/A |
| Kubernetes | ✓ | N/A |
| LangChain | N/A | N/A |
| PyTorch | N/A | N/A |
Pricing comparison: KPMG vs SoftKraft
| Criterion | KPMG | SoftKraft |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Retainer, Dedicated team | Fixed project, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: KPMG vs SoftKraft
| Dimension | KPMG | SoftKraft |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Financial services, Healthcare, Manufacturing | Fintech, SaaS, Healthtech |
| Best use cases | Adopting a named, productized AI tool rather than commissioning a fully bespoke build., Running an AI workforce transformation program alongside existing KPMG advisory work. | Getting an AI strategy assessment for a pre-seed or seed-stage startup., Getting AI consulting and data engineering handled by one small, accountable team. |
| Typical project type | Retainer | Fixed project |
KPMG vs SoftKraft: pros and cons
| KPMG | |
|---|---|
| + | 251,000-plus person global scale supports the largest enterprise engagements. |
| + | Named, productized AI tools (aIQ, Mystro) give clients something more concrete to evaluate than a generic strategy deck. |
| + | Nearly 130 years of institutional history dating back to 1897. |
| + | Global headquarters in London simplifies EU and UK contracting. |
| - | Reported headcount varies by roughly 25,000 across different reporting periods |
| - | Big Four pricing and engagement minimums put it out of reach for most small and mid-size buyers |
| 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 KPMG?
A typical fit: adopting a named, productized AI tool rather than commissioning a fully bespoke build.
Named AI products (aIQ, Mystro) rather than purely bespoke consulting engagements. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Manufacturing, Government.
Who should choose SoftKraft?
A typical fit: getting an 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: KPMG vs SoftKraft
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | SoftKraft |
| You need a large dedicated team for an ongoing programme | KPMG |
| Your budget is at the lower end | Compare: KPMG (Not disclosed) vs SoftKraft (Not disclosed) |
| You need specialist depth in a specific vertical | KPMG |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | KPMG |
Use case fit: KPMG vs SoftKraft
| Use case | KPMG fit | SoftKraft fit | Winner |
|---|---|---|---|
| Adopting a named, productized AI tool rather than commissioning a fully bespoke build. | Strong | Limited | KPMG |
| Running an AI workforce transformation program alongside existing KPMG advisory work. | Strong | Limited | KPMG |
| Getting an AI strategy assessment for a pre-seed or seed-stage startup. | Limited | Strong | SoftKraft |
| Getting AI consulting and data engineering handled by one small, accountable team. | Limited | Strong | SoftKraft |
| Fixed-price project | Limited | Limited | Both equally |
| Dedicated team model | Limited | Limited | Both equally |
Verdict: KPMG vs SoftKraft
KPMG (4.1/5) is the stronger overall choice for most AI Consulting projects. Named AI products (aIQ, Mystro) rather than purely bespoke consulting engagements.
SoftKraft (3.9/5) is worth a look if you need getting AI consulting and data engineering handled by one small, accountable team. If your situation matches that, SoftKraft is a competitive option.
Related comparisons
KPMG vs SoftKraft FAQ
Is KPMG better than SoftKraft?
KPMG (4.1/5) scores higher overall, but "better" depends on your use case. KPMG's strongest advantage: 251,000-plus person global scale supports the largest enterprise engagements. SoftKraft's strongest advantage: smaller team size keeps overhead, and likely cost, below mid-size and enterprise consultancies.
How do KPMG and SoftKraft differ in pricing?
KPMG uses retainer, enterprise contracting 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: KPMG or SoftKraft?
KPMG 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 KPMG and SoftKraft?
KPMG's primary differentiator is: named AI products (aIQ, Mystro) rather than purely bespoke consulting engagements. SoftKraft's primary differentiator is: small dedicated team priced for startup budgets, not enterprise rates. They also differ in team size (251,000-275,000 vs 11-50), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Healthcare vs Fintech, SaaS).
Verify all details directly with each company before making a decision.