Quantiphi vs Azumo: full comparison for 2026
Quick verdict
Quantiphi (4.3/5) edges ahead of Azumo (4.0/5) overall. Quantiphi is the better choice for large document-heavy programs on Google Cloud or AWS. Azumo is the stronger option for U.S. startups wanting nearshore AI engineers. The right choice depends on your project size, budget, and required tech stack.
Quantiphi vs Azumo: head-to-head summary
| Criterion | Quantiphi | Azumo |
|---|---|---|
| Founded | 2013 | 2016 |
| HQ | Marlborough, MA, USA | San Francisco, CA, USA |
| Team size | 3,500+ | 80+ |
| Rating | 4.3 / 5 | 4.0 / 5 |
| Primary differentiator | Partner-of-the-year history with both Google Cloud and AWS on AI work | Latin American engineers working U.S. hours |
| Pricing model | Fixed-scope projects, time & materials, and dedicated teams; rates on request | Dedicated teams and time & materials; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Vertex AI, AWS Bedrock, Snowflake | Azure OpenAI, AWS Bedrock, LangChain |
| Industries served | Healthcare, Insurance, Financial services, Public sector, Media | SaaS, Media, Healthcare, Financial services |
Quantiphi vs Azumo: overview
Quantiphi
Quantiphi was founded in 2013, is headquartered in Marlborough, Massachusetts, and employs over 3,500 people, most of them in India. It reports 21 Google Cloud Partner of the Year awards over ten years and three AWS AI/ML Partner of the Year awards (per company materials; independently unverifiable). Document AI, contact-center AI, and healthcare and insurance workflows make up much of its integration work. Its size lets it staff large programs while still working only on AI and data.
Azumo
Azumo is a nearshore software firm based in San Francisco, founded in 2016, with engineers across Latin America. Built In lists 79 employees, while other directories show 201–500, so its size is unclear. The company works on AI, data engineering, cloud, and mobile, and cites more than 350 delivered projects (per G2 profile; independently unverifiable). U.S. companies that want daily overlap with an outside team at nearshore rates are its main buyers.
Services and capabilities: Quantiphi vs Azumo
| Capability | Quantiphi | Azumo |
|---|---|---|
| CRM / ERP integration | ✗ | ✗ |
| LLM API gateway & cost control | ✗ | ✓ |
| Document processing | ✓ | ✗ |
| Conversational AI | ✓ | ✓ |
| Agentic workflows | ✗ | ✗ |
| Fixed-price pilot | ✗ | ✗ |
| Managed services after launch | ✗ | ✗ |
Tech stack comparison: Quantiphi vs Azumo
| Framework / platform | Quantiphi | Azumo |
|---|---|---|
| Salesforce | N/A | N/A |
| SAP | N/A | N/A |
| Microsoft Dynamics 365 | N/A | N/A |
| HubSpot | N/A | N/A |
| Snowflake | ✓ | ✓ |
| Databricks | N/A | N/A |
| BigQuery | ✓ | N/A |
| Azure OpenAI | N/A | ✓ |
| AWS Bedrock | ✓ | ✓ |
| Zendesk | N/A | N/A |
Pricing comparison: Quantiphi vs Azumo
| Criterion | Quantiphi | Azumo |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed-scope project, Time & materials, Dedicated team | Dedicated team, Time & materials |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Quantiphi vs Azumo
| Dimension | Quantiphi | Azumo |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Healthcare, Insurance, Financial services | SaaS, Media, Healthcare |
| Best use cases | Claims and medical-record extraction for insurers, Contact-center assistants on Google Cloud | Adding a chat assistant to a SaaS product, Extending an in-house team with LLM engineers |
| Typical project type | Fixed-scope project | Dedicated team |
Quantiphi vs Azumo: pros and cons
| Quantiphi | |
|---|---|
| + | Partner depth on two hyperscalers instead of one. |
| + | Document AI and contact-center AI are mature practice areas. |
| + | Enough staff to run several workstreams in parallel. |
| + | A multi-year Google Cloud partnership announced in 2026 covers joint industry solutions. |
| - | Most delivery is offshore, so time-zone overlap with U.S. or EU teams is partial |
| - | Fixed-price pilots aren't advertised as a standard entry point |
| - | Award counts come from the company itself |
| Azumo | |
|---|---|
| + | Full time-zone overlap with U.S. clients. |
| + | Nearshore rates below U.S. onshore firms. |
| + | Mixes AI work with the app and data engineering around it. |
| - | Team size is reported anywhere from about 80 to 500 |
| - | No platform partner tiers to verify |
| - | No fixed-price pilot or managed-service offer published |
Who should choose Quantiphi?
A typical fit: claims and medical-record extraction for insurers.
Partner-of-the-year history with both Google Cloud and AWS on AI work. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Insurance, Financial services, Public sector, Media.
Who should choose Azumo?
A typical fit: adding a chat assistant to a SaaS product.
Latin American engineers working U.S. hours. Minimum engagement is not publicly disclosed. Works best with clients in SaaS, Media, Healthcare, Financial services.
Decision matrix: Quantiphi vs Azumo
| Your situation | Recommended choice |
|---|---|
| You want a priced pilot before committing to a rollout | Neither advertises one; ask for a scoped pilot quote |
| You need someone to run and monitor the system after launch | Neither; plan for your own team to run it |
| Your budget is at the lower end | Compare: Quantiphi (Not disclosed) vs Azumo (Not disclosed) |
| The AI has to read and write in your CRM or ERP | Check each profile; neither lists CRM or ERP work |
| You need multi-step agents acting across systems | Neither lists agentic work |
| You need a large team for a multi-year program | Quantiphi |
Use case fit: Quantiphi vs Azumo
| Use case | Quantiphi fit | Azumo fit | Winner |
|---|---|---|---|
| Claims and medical-record extraction for insurers | Strong | Limited | Quantiphi |
| Contact-center assistants on Google Cloud | Strong | Limited | Quantiphi |
| Adding a chat assistant to a SaaS product | Limited | Strong | Azumo |
| Extending an in-house team with LLM engineers | Limited | Strong | Azumo |
Verdict: Quantiphi vs Azumo
Quantiphi (4.3/5) is the stronger overall choice for most AI Integration Services projects. Partner-of-the-year history with both Google Cloud and AWS on AI work.
Azumo (4.0/5) is worth a look if you need extending an in-house team with LLM engineers. If your situation matches that, Azumo is a competitive option.
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Quantiphi vs Azumo FAQ
Is Quantiphi better than Azumo?
Quantiphi (4.3/5) scores higher overall, but "better" depends on your use case. Quantiphi's strongest advantage: partner depth on two hyperscalers instead of one. Azumo's strongest advantage: full time-zone overlap with U.S. clients.
How do Quantiphi and Azumo differ in pricing?
Quantiphi's pricing: fixed-scope projects, time & materials, and dedicated teams; rates on request. Azumo's pricing: dedicated teams and time & materials; rates on request. 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 Azumo?
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 provider before shortlisting.
What are the main differences between Quantiphi and Azumo?
Quantiphi's primary differentiator is: partner-of-the-year history with both Google Cloud and AWS on AI work. Azumo's primary differentiator is: latin American engineers working U.S. hours. They also differ in team size (3,500+ vs 80+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Healthcare, Insurance vs SaaS, Media).
Verify all details directly with each provider before making a decision.