Fractal vs Tiger Analytics: full comparison for 2026
Quick verdict
Fractal (4.5/5) edges ahead of Tiger Analytics (4.1/5) overall. Fractal is the better choice for consumer and financial firms wanting AI depth from one partner. Tiger Analytics is the stronger option for enterprises wanting strategy plus lower-cost offshore delivery. The right choice depends on the size of your program, your budget, and whether you want the same firm to build what it recommends.
Fractal vs Tiger Analytics: head-to-head summary
| Criterion | Fractal | Tiger Analytics |
|---|---|---|
| Founded | 2000 | 2011 |
| HQ | Mumbai, India / New York, USA | Santa Clara, USA |
| Team size | 5,000+ | 4,000+ |
| Rating | 4.5 / 5 | 4.1 / 5 |
| Primary differentiator | Twenty-five years of AI and analytics delivery behind its strategy work, with its own platforms to build on | AI roadmap work that feeds directly into large India-based data science teams |
| Pricing model | Project and managed-program fees; rates not published | Project and dedicated-team pricing; rates not published |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Cogentiq, Azure, AWS | Azure, AWS, Google Cloud |
| Industries served | Consumer goods, Retail, Financial services, Insurance, Healthcare, Technology | Consumer goods, Retail, Insurance, Banking, Manufacturing, Healthcare |
Fractal vs Tiger Analytics: overview
Fractal
Founded in Mumbai in 2000, Fractal calls itself a pure-play enterprise AI company and runs its US business from New York. It has more than 5,000 employees across 18 locations and listed on India's stock exchanges in February 2026, with TPG and Apax among the selling shareholders. Consulting work starts with use-case discovery and value cases, then moves into data science, engineering, and its own products such as the Cogentiq agent platform. Forrester named it a Leader in its Customer Analytics Services Wave for Q2 2025, according to Fractal's announcement. That history is what you pay for. Few firms have run AI programs for consumer and financial clients this long, although the advice tends to lead into Fractal's own platforms.
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.
Services and capabilities: Fractal vs Tiger Analytics
| Capability | Fractal | Tiger Analytics |
|---|---|---|
| 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: Fractal vs Tiger Analytics
| Framework / platform | Fractal | Tiger Analytics |
|---|---|---|
| EU AI Act | N/A | N/A |
| GDPR | N/A | N/A |
| NIST AI RMF | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | ✓ |
| Databricks | ✓ | ✓ |
| Snowflake | ✓ | ✓ |
Pricing comparison: Fractal vs Tiger Analytics
| Criterion | Fractal | Tiger Analytics |
|---|---|---|
| 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: Fractal vs Tiger Analytics
| Dimension | Fractal | Tiger Analytics |
|---|---|---|
| Best company size | Mid-market to enterprise | Mid-market to enterprise |
| Best industries | Consumer goods, Retail, Financial services | Consumer goods, Retail, Insurance |
| Best use cases | Prioritizing AI use cases across marketing, supply chain, and pricing at a consumer goods company., Building customer analytics and personalization models after a strategy phase. | Analytics and AI roadmaps for consumer goods and retail companies., Demand forecasting and pricing models after a planning phase. |
| Typical project type | Strategy & roadmap engagement | Strategy & roadmap engagement |
Fractal vs Tiger Analytics: pros and cons
| Fractal | |
|---|---|
| + | Has done AI and analytics work since 2000, longer than most firms on this list have existed |
| + | Strategy hands straight to data science and engineering teams inside the same company |
| + | Named a Leader in Forrester's customer analytics services evaluation (Q2 2025) |
| + | Public since February 2026, so its financials and ownership are disclosed |
| + | Long record with consumer goods and retail clients on demand, pricing, and marketing models |
| - | Strategy work tends to lead into its own platforms and delivery teams, which narrows your vendor choice later |
| - | Governance and EU AI Act advice is less visible than its analytics and engineering work |
| - | Listed in 2026 after years of private equity ownership (TPG, Apax), so check continuity of the team you will get |
| 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 |
Who should choose Fractal?
A typical fit: prioritizing AI use cases across marketing, supply chain, and pricing at a consumer goods company.
Twenty-five years of AI and analytics delivery behind its strategy work, with its own platforms to build on. Minimum engagement is not publicly disclosed. Works best with clients in Consumer goods, Retail, Financial services, Insurance, Healthcare, Technology.
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.
Decision matrix: Fractal vs Tiger Analytics
| Your situation | Recommended choice |
|---|---|
| Your board wants a costed, sequenced roadmap within a quarter | Both price and rank use cases |
| 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: Fractal (Not disclosed) vs Tiger Analytics (Not disclosed) |
| You need a large team across many countries | Fractal |
Use case fit: Fractal vs Tiger Analytics
| Use case | Fractal fit | Tiger Analytics fit | Winner |
|---|---|---|---|
| Prioritizing AI use cases across marketing, supply chain, and pricing at a consumer goods company. | Strong | Limited | Fractal |
| Building customer analytics and personalization models after a strategy phase. | Strong | Limited | Fractal |
| Analytics and AI roadmaps for consumer goods and retail companies. | Limited | Strong | Tiger Analytics |
| Demand forecasting and pricing models after a planning phase. | Limited | Strong | Tiger Analytics |
Verdict: Fractal vs Tiger Analytics
Fractal (4.5/5) is the stronger overall choice for most AI Strategy Consulting projects. Twenty-five years of AI and analytics delivery behind its strategy work, with its own platforms to build on.
Tiger Analytics (4.1/5) is worth a look if you need demand forecasting and pricing models after a planning phase. If your situation matches that, Tiger Analytics is a competitive option.
Related comparisons
Fractal vs Tiger Analytics FAQ
Is Fractal better than Tiger Analytics?
Fractal (4.5/5) scores higher overall, but "better" depends on your use case. Fractal's strongest advantage: has done AI and analytics work since 2000, longer than most firms on this list have existed. Tiger Analytics's strongest advantage: delivery costs after the strategy are lower than at US or European firms.
How do Fractal and Tiger Analytics differ in pricing?
Fractal's pricing: project and managed-program fees; rates not published. Tiger Analytics'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: Fractal or Tiger Analytics?
Fractal 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 Fractal and Tiger Analytics?
Fractal's primary differentiator is: twenty-five years of AI and analytics delivery behind its strategy work, with its own platforms to build on. Tiger Analytics's primary differentiator is: AI roadmap work that feeds directly into large India-based data science teams. They also differ in team size (5,000+ vs 4,000+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Consumer goods, Retail vs Consumer goods, Retail).
Verify all details directly with each consultant before making a decision.