Quantiphi vs deepsense.ai: full comparison for 2026
Quick verdict
Quantiphi (4.0/5) edges ahead of deepsense.ai (3.9/5) overall. Quantiphi is the better choice for companies committed to Google Cloud or AWS. deepsense.ai is the stronger option for technical teams wanting AI strategy from model builders. The right choice depends on the size of your program, your budget, and whether you want the same firm to build what it recommends.
Quantiphi vs deepsense.ai: head-to-head summary
| Criterion | Quantiphi | deepsense.ai |
|---|---|---|
| Founded | 2013 | 2014 |
| HQ | Marlborough, USA | Warsaw, Poland |
| Team size | 4,000 | 120+ |
| Rating | 4.0 / 5 | 3.9 / 5 |
| Primary differentiator | Use-case discovery from a top-tier Google Cloud and AWS engineering partner | Strategy workshops run by engineers who build vision and language models |
| Pricing model | Project and dedicated-team pricing; rates not published | $100–$149/hr (Clutch band); project-based |
| Min. engagement | Not disclosed | $25,000+ (Clutch) |
| Primary tech stack | Google Cloud, AWS, NVIDIA | Python, PyTorch, AWS |
| Industries served | Healthcare, Financial services, Insurance, Media, Public sector, Retail | Retail, Manufacturing, Financial services, Healthcare, Media |
Quantiphi vs deepsense.ai: overview
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.
deepsense.ai
deepsense.ai was founded in 2014 in Warsaw and has an office in Palo Alto, with about 120 AI specialists, several of them Kaggle competition winners (per company website; independently unverifiable). It sells AI strategy consulting and workshops, though most of its work is engineering: computer vision, language models, and predictive systems. Clutch lists rates of $100–$149 an hour and a $25,000+ minimum project. That puts it at the top end for a Central European firm.
Services and capabilities: Quantiphi vs deepsense.ai
| Capability | Quantiphi | deepsense.ai |
|---|---|---|
| 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: Quantiphi vs deepsense.ai
| Framework / platform | Quantiphi | deepsense.ai |
|---|---|---|
| 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 | N/A |
| Snowflake | ✓ | N/A |
Pricing comparison: Quantiphi vs deepsense.ai
| Criterion | Quantiphi | deepsense.ai |
|---|---|---|
| Minimum engagement | Not disclosed | $25,000+ (Clutch) |
| Engagement models | Strategy & roadmap engagement, Delivery team | Strategy & roadmap engagement, Delivery team |
| Rate transparency | Not public | Minimum disclosed |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Quantiphi vs deepsense.ai
| Dimension | Quantiphi | deepsense.ai |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Healthcare, Financial services, Insurance | Retail, Manufacturing, Financial services |
| Best use cases | AI roadmaps for companies already standardized on Google Cloud., Document and speech AI for healthcare and insurance. | Workshops to pick a first computer vision or language model project., Technical feasibility reviews for an AI product idea. |
| Typical project type | Strategy & roadmap engagement | Strategy & roadmap engagement |
Quantiphi vs deepsense.ai: pros and cons
| 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 |
| deepsense.ai | |
|---|---|
| + | Workshops are run by people who build models, so feasibility advice is concrete |
| + | Strong research background in computer vision and language models |
| + | Offers AI training for client teams |
| + | Published Clutch rates make budgeting easier |
| - | Strategy is a small part of an engineering-led business |
| - | Higher Clutch rate band than most Polish peers |
| - | No change-management practice |
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.
Who should choose deepsense.ai?
A typical fit: workshops to pick a first computer vision or language model project.
Strategy workshops run by engineers who build vision and language models. Minimum engagement starts at $25,000+ (Clutch). Works best with clients in Retail, Manufacturing, Financial services, Healthcare, Media.
Decision matrix: Quantiphi vs deepsense.ai
| 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 | Neither lists governance work; add a specialist |
| AI will change roles and processes for many staff | Neither; plan change management separately |
| You want the strategy firm to build the result too | Both can deliver after the strategy |
| Your budget is at the lower end | Compare: Quantiphi (Not disclosed) vs deepsense.ai ($25,000+ (Clutch)) |
| You need a large team across many countries | Quantiphi |
Use case fit: Quantiphi vs deepsense.ai
| Use case | Quantiphi fit | deepsense.ai fit | Winner |
|---|---|---|---|
| AI roadmaps for companies already standardized on Google Cloud. | Strong | Limited | Quantiphi |
| Document and speech AI for healthcare and insurance. | Strong | Limited | Quantiphi |
| Workshops to pick a first computer vision or language model project. | Limited | Strong | deepsense.ai |
| Technical feasibility reviews for an AI product idea. | Limited | Strong | deepsense.ai |
Verdict: Quantiphi vs deepsense.ai
Quantiphi (4.0/5) is the stronger overall choice for most AI Strategy Consulting projects. Use-case discovery from a top-tier Google Cloud and AWS engineering partner.
deepsense.ai (3.9/5) is worth a look if you need technical feasibility reviews for an AI product idea. If your situation matches that, deepsense.ai is a competitive option.
Related comparisons
Quantiphi vs deepsense.ai FAQ
Is Quantiphi better than deepsense.ai?
Quantiphi (4.0/5) scores higher overall, but "better" depends on your use case. Quantiphi's strongest advantage: deep Google Cloud expertise, confirmed by ISG's 2024 Provider Lens report. deepsense.ai's strongest advantage: workshops are run by people who build models, so feasibility advice is concrete.
How do Quantiphi and deepsense.ai differ in pricing?
Quantiphi's pricing: project and dedicated-team pricing; rates not published. deepsense.ai's pricing: $100–$149/hr (Clutch band); project-based with a minimum engagement of $25,000+ (Clutch). 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: Quantiphi or deepsense.ai?
Quantiphi 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 Quantiphi and deepsense.ai?
Quantiphi's primary differentiator is: use-case discovery from a top-tier Google Cloud and AWS engineering partner. deepsense.ai's primary differentiator is: strategy workshops run by engineers who build vision and language models. They also differ in team size (4,000 vs 120+), minimum engagement (Not disclosed vs $25,000+ (Clutch)), and primary industries served (Healthcare, Financial services vs Retail, Manufacturing).
Verify all details directly with each consultant before making a decision.