Top AI Strategy Consultants

Tiger Analytics vs Quantiphi: full comparison for 2026

Quick verdict

Tiger Analytics (4.1/5) edges ahead of Quantiphi (4.0/5) overall. Tiger Analytics is the better choice for enterprises wanting strategy plus lower-cost offshore delivery. 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.

Tiger Analytics vs Quantiphi: head-to-head summary

Criterion Tiger Analytics Quantiphi
Founded 2011 2013
HQ Santa Clara, USA Marlborough, USA
Team size 4,000+ 4,000
Rating 4.1 / 5 4.0 / 5
Primary differentiator AI roadmap work that feeds directly into large India-based data science teams Use-case discovery from a top-tier Google Cloud and AWS engineering partner
Pricing model Project and dedicated-team pricing; rates not published Project and dedicated-team pricing; rates not published
Min. engagement Not disclosed Not disclosed
Primary tech stack Azure, AWS, Google Cloud Google Cloud, AWS, NVIDIA
Industries served Consumer goods, Retail, Insurance, Banking, Manufacturing, Healthcare Healthcare, Financial services, Insurance, Media, Public sector, Retail

Tiger Analytics vs Quantiphi: overview

Tiger Analytics

Tiger Analytics was founded in 2011, is based in Santa Clara, California, and says it has 4,000+ technologists and consultants, most of them delivering from India (per company website; independently unverifiable). It is privately held. Strategy work usually takes the form of an AI or analytics roadmap that leads into data science and engineering projects run by its own teams. The appeal is cost after the plan is agreed: offshore delivery keeps the build affordable.

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: Tiger Analytics vs Quantiphi

Capability Tiger Analytics 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: Tiger Analytics vs Quantiphi

Framework / platform Tiger Analytics 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: Tiger Analytics vs Quantiphi

Criterion Tiger Analytics Quantiphi
Minimum engagement Not disclosed Not disclosed
Engagement models Strategy & roadmap engagement, Delivery team Strategy & roadmap engagement, Delivery team
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: Tiger Analytics vs Quantiphi

Dimension Tiger Analytics Quantiphi
Best company size Mid-market to enterprise Mid-market to enterprise
Best industries Consumer goods, Retail, Insurance Healthcare, Financial services, Insurance
Best use cases Analytics and AI roadmaps for consumer goods and retail companies., Demand forecasting and pricing models after a planning phase. 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

Tiger Analytics vs Quantiphi: pros and cons

Tiger Analytics
+ Delivery costs after the strategy are lower than at US or European firms
+ Large data science bench for forecasting, pricing, and marketing models
+ Privately held and focused on AI and analytics alone
+ Cost modeling is part of how it sizes use cases
- Strategy work is mainly a front end to its delivery business
- Change management and organizational design are not core practices
- Time-zone gaps between India-based teams and US or European clients
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 Tiger Analytics?

A typical fit: analytics and AI roadmaps for consumer goods and retail companies.

AI roadmap work that feeds directly into large India-based data science teams. Minimum engagement is not publicly disclosed. Works best with clients in Consumer goods, Retail, Insurance, Banking, Manufacturing, Healthcare.

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: Tiger Analytics vs Quantiphi

Your situation Recommended choice
Your board wants a costed, sequenced roadmap within a quarter Tiger Analytics
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: Tiger Analytics (Not disclosed) vs Quantiphi (Not disclosed)
You need a large team across many countries Tiger Analytics

Use case fit: Tiger Analytics vs Quantiphi

Use case Tiger Analytics fit Quantiphi fit Winner
Analytics and AI roadmaps for consumer goods and retail companies. Strong Limited Tiger Analytics
Demand forecasting and pricing models after a planning phase. Strong Limited Tiger Analytics
AI roadmaps for companies already standardized on Google Cloud. Limited Strong Quantiphi
Document and speech AI for healthcare and insurance. Limited Strong Quantiphi

Verdict: Tiger Analytics vs Quantiphi

Tiger Analytics (4.1/5) is the stronger overall choice for most AI Strategy Consulting projects. AI roadmap work that feeds directly into large India-based data science teams.

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.

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Tiger Analytics vs Quantiphi FAQ

Is Tiger Analytics better than Quantiphi?

Tiger Analytics (4.1/5) scores higher overall, but "better" depends on your use case. Tiger Analytics's strongest advantage: delivery costs after the strategy are lower than at US or European firms. Quantiphi's strongest advantage: deep Google Cloud expertise, confirmed by ISG's 2024 Provider Lens report.

How do Tiger Analytics and Quantiphi differ in pricing?

Tiger Analytics's pricing: project and dedicated-team pricing; 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: Tiger Analytics or Quantiphi?

Tiger Analytics 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 Tiger Analytics and Quantiphi?

Tiger Analytics's primary differentiator is: AI roadmap work that feeds directly into large India-based data science teams. Quantiphi's primary differentiator is: use-case discovery from a top-tier Google Cloud and AWS engineering partner. They also differ in team size (4,000+ vs 4,000), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Consumer goods, Retail vs Healthcare, Financial services).

Verify all details directly with each consultant before making a decision.