Slalom vs Quantiphi: full comparison for 2026
Quick verdict
Slalom (4.1/5) edges ahead of Quantiphi (4.0/5) overall. Slalom is the better choice for north American firms wanting local, on-site AI consultants. Quantiphi is the stronger option for companies committed to Google Cloud or AWS. The right choice depends on the size of your program, your budget, and whether you want the same firm to build what it recommends.
Slalom vs Quantiphi: head-to-head summary
| Criterion | Slalom | Quantiphi |
|---|---|---|
| Founded | 2001 | 2013 |
| HQ | Seattle, USA | Marlborough, USA |
| Team size | 10,000+ | 4,000 |
| Rating | 4.1 / 5 | 4.0 / 5 |
| Primary differentiator | Local-office model that puts strategy consultants on-site, with deep cloud partnerships behind them | Use-case discovery from a top-tier Google Cloud and AWS engineering partner |
| Pricing model | Time & materials and fixed-fee projects; rates not published | Project and dedicated-team pricing; rates not published |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | AWS, Azure, Google Cloud | Google Cloud, AWS, NVIDIA |
| Industries served | Financial services, Healthcare, Retail, Manufacturing, Public sector, Technology | Healthcare, Financial services, Insurance, Media, Public sector, Retail |
Slalom vs Quantiphi: overview
Slalom
Slalom was founded in Seattle in 2001 and has more than 10,000 employees in over 50 offices across the Americas, Europe, and Asia. In August 2026 it hired a former Accenture executive as its chief AI officer. Its AI strategy practice covers operating models, governance, and data strategy, delivered by local teams who work on-site with clients. Partnerships with Microsoft, AWS, Google Cloud, Snowflake, and Salesforce mean a Slalom roadmap usually lands on one of those platforms.
Quantiphi
Quantiphi was founded in 2013, is headquartered in Marlborough, Massachusetts, and has around 4,000 employees. It holds top partner tiers with Google Cloud, AWS, and NVIDIA, according to its own materials, and ISG named it a Leader for AI and machine learning services on Google Cloud in its 2024 Provider Lens report. Its strategy offer is mostly a front end to engineering: use-case discovery and roadmaps that lead into builds on those platforms. It makes most sense when the platform decision is already made.
Services and capabilities: Slalom vs Quantiphi
| Capability | Slalom | Quantiphi |
|---|---|---|
| Readiness assessment | ✗ | ✓ |
| Use-case prioritization | ✗ | ✓ |
| TCO / ROI modeling | ✗ | ✗ |
| AI governance & EU AI Act | ✓ | ✗ |
| Build vs. buy advice | ✗ | ✗ |
| Audit of live AI programs | ✗ | ✗ |
| Change management | ✓ | ✗ |
| Can build what it recommends | ✓ | ✓ |
Frameworks and platforms: Slalom vs Quantiphi
| Framework / platform | Slalom | Quantiphi |
|---|---|---|
| EU AI Act | N/A | N/A |
| GDPR | N/A | N/A |
| NIST AI RMF | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | ✓ | ✓ |
| Databricks | ✓ | N/A |
| Snowflake | ✓ | ✓ |
Pricing comparison: Slalom vs Quantiphi
| Criterion | Slalom | Quantiphi |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Strategy & roadmap engagement, Delivery team, Ongoing advisory | Strategy & roadmap engagement, Delivery team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Slalom vs Quantiphi
| Dimension | Slalom | Quantiphi |
|---|---|---|
| Best company size | Enterprise | Mid-market to enterprise |
| Best industries | Financial services, Healthcare, Retail | Healthcare, Financial services, Insurance |
| Best use cases | AI and data strategy for a North American mid-size or large company., Governance and operating-model design for a first wave of AI projects. | AI roadmaps for companies already standardized on Google Cloud., Document and speech AI for healthcare and insurance. |
| Typical project type | Strategy & roadmap engagement | Strategy & roadmap engagement |
Slalom vs Quantiphi: pros and cons
| Slalom | |
|---|---|
| + | Consultants live in the client's city, which makes workshops and on-site discovery easy |
| + | Covers operating model and governance as well as technology |
| + | Strong standing with Microsoft, AWS, Google Cloud, and Snowflake |
| + | Can staff the build after the strategy without changing firms |
| - | Roadmaps tend to land on its partner platforms |
| - | New AI leadership (August 2026) means the practice direction is still settling |
| - | Less depth on EU regulation than European consultancies |
| Quantiphi | |
|---|---|
| + | Deep Google Cloud expertise, confirmed by ISG's 2024 Provider Lens report |
| + | Moves from discovery to build without changing vendors |
| + | Large engineering bench for document, speech, and vision projects |
| + | Experience with healthcare and public-sector data |
| - | Advice is shaped by its platform partnerships |
| - | Little board-level or organizational change work |
| - | Partner-tier claims come from its own recruiting material, with ISG's report as the independent check |
Who should choose Slalom?
A typical fit: AI and data strategy for a North American mid-size or large company.
Local-office model that puts strategy consultants on-site, with deep cloud partnerships behind them. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Retail, Manufacturing, Public sector, Technology.
Who should choose Quantiphi?
A typical fit: AI roadmaps for companies already standardized on Google Cloud.
Use-case discovery from a top-tier Google Cloud and AWS engineering partner. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Financial services, Insurance, Media, Public sector, Retail.
Decision matrix: Slalom vs Quantiphi
| Your situation | Recommended choice |
|---|---|
| Your board wants a costed, sequenced roadmap within a quarter | Neither lists cost modeling; ask for a sample roadmap |
| You already run AI that is missing its targets | Neither offers a separate audit; ask for a scoped review |
| Regulators will ask how each AI system is governed | Slalom |
| AI will change roles and processes for many staff | Slalom |
| You want the strategy firm to build the result too | Both can deliver after the strategy |
| Your budget is at the lower end | Compare: Slalom (Not disclosed) vs Quantiphi (Not disclosed) |
| You need a large team across many countries | Slalom |
Use case fit: Slalom vs Quantiphi
| Use case | Slalom fit | Quantiphi fit | Winner |
|---|---|---|---|
| AI and data strategy for a North American mid-size or large company. | Strong | Limited | Slalom |
| Governance and operating-model design for a first wave of AI projects. | Strong | Limited | Slalom |
| AI roadmaps for companies already standardized on Google Cloud. | Limited | Strong | Quantiphi |
| Document and speech AI for healthcare and insurance. | Limited | Strong | Quantiphi |
Verdict: Slalom vs Quantiphi
Slalom (4.1/5) is the stronger overall choice for most AI Strategy Consulting projects. Local-office model that puts strategy consultants on-site, with deep cloud partnerships behind them.
Quantiphi (4.0/5) is worth a look if you need document and speech AI for healthcare and insurance. If your situation matches that, Quantiphi is a competitive option.
Related comparisons
Slalom vs Quantiphi FAQ
Is Slalom better than Quantiphi?
Slalom (4.1/5) scores higher overall, but "better" depends on your use case. Slalom's strongest advantage: consultants live in the client's city, which makes workshops and on-site discovery easy. Quantiphi's strongest advantage: deep Google Cloud expertise, confirmed by ISG's 2024 Provider Lens report.
How do Slalom and Quantiphi differ in pricing?
Slalom's pricing: time & materials and fixed-fee projects; rates not published. Quantiphi's pricing: project and dedicated-team pricing; rates not published. Any hourly bands shown come from Clutch, not a published rate card, so a scoping call is still needed for a project quote.
Which is better for enterprise: Slalom or Quantiphi?
Slalom is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each consultant before shortlisting.
What are the main differences between Slalom and Quantiphi?
Slalom's primary differentiator is: local-office model that puts strategy consultants on-site, with deep cloud partnerships behind them. Quantiphi's primary differentiator is: use-case discovery from a top-tier Google Cloud and AWS engineering partner. They also differ in team size (10,000+ vs 4,000), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Healthcare vs Healthcare, Financial services).
Verify all details directly with each consultant before making a decision.