Quantiphi vs Addepto: full comparison for 2026
Quick verdict
Quantiphi (4.3/5) edges ahead of Addepto (4.3/5) overall. Quantiphi is the better choice for large document-heavy programs on Google Cloud or AWS. Addepto is the stronger option for manufacturers connecting AI to engineering data. The right choice depends on your project size, budget, and required tech stack.
Quantiphi vs Addepto: head-to-head summary
| Criterion | Quantiphi | Addepto |
|---|---|---|
| Founded | 2013 | 2018 |
| HQ | Marlborough, MA, USA | Warsaw, Poland |
| Team size | 3,500+ | 50–249 |
| Rating | 4.3 / 5 | 4.3 / 5 |
| Primary differentiator | Partner-of-the-year history with both Google Cloud and AWS on AI work | Integration work with industrial systems such as SCADA, CAD, and PLM |
| Pricing model | Fixed-scope projects, time & materials, and dedicated teams; rates on request | Fixed-scope projects and time & materials; $50–$99/hr (Clutch band) |
| Min. engagement | Not disclosed | $10,000+ (Clutch) |
| Primary tech stack | Vertex AI, AWS Bedrock, Snowflake | Databricks, Azure OpenAI, Snowflake |
| Industries served | Healthcare, Insurance, Financial services, Public sector, Media | Manufacturing, Energy, Logistics, Retail & e-commerce |
Quantiphi vs Addepto: 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.
Addepto
Addepto was founded in Warsaw in 2018 and employs 50–100 people according to most directories (Clutch shows 50–249). KMS Technology acquired it in December 2025, and it continues as an independent subsidiary. Its focus is unusual. The integration work leans toward industrial and engineering data, connecting AI to supervisory control (SCADA), computer-aided design (CAD), and product lifecycle management (PLM) systems alongside more common document and analytics projects. Clutch lists a $10,000 minimum and a $50–$99 hourly band, one of the more accessible entry points on this list.
Services and capabilities: Quantiphi vs Addepto
| Capability | Quantiphi | Addepto |
|---|---|---|
| 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 Addepto
| Framework / platform | Quantiphi | Addepto |
|---|---|---|
| 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 | ✓ |
| BigQuery | ✓ | N/A |
| Azure OpenAI | N/A | ✓ |
| AWS Bedrock | ✓ | N/A |
| Zendesk | N/A | N/A |
Pricing comparison: Quantiphi vs Addepto
| Criterion | Quantiphi | Addepto |
|---|---|---|
| Minimum engagement | Not disclosed | $10,000+ (Clutch) |
| Engagement models | Fixed-scope project, Time & materials, Dedicated team | Fixed-scope project, Time & materials |
| Rate transparency | Not public | Minimum disclosed |
| Price tier | Mid-market | Accessible |
Target audience comparison: Quantiphi vs Addepto
| Dimension | Quantiphi | Addepto |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Healthcare, Insurance, Financial services | Manufacturing, Energy, Logistics |
| Best use cases | Claims and medical-record extraction for insurers, Contact-center assistants on Google Cloud | Search across CAD and PLM records with an LLM front end, Predictive maintenance from SCADA sensor history |
| Typical project type | Fixed-scope project | Fixed-scope project |
Quantiphi vs Addepto: 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 |
| Addepto | |
|---|---|
| + | The $10K Clutch minimum lets small teams test an integration without a large commitment. |
| + | Experience with plant and engineering systems most AI vendors don't touch. |
| + | Clutch reviews average close to 4.9. |
| + | Data engineering and AI are scoped by the same team. |
| - | Acquired by KMS Technology in December 2025; long-term pricing and branding may change |
| - | Headcount varies a lot between directories |
| - | No managed-service offer for running systems after launch |
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 Addepto?
A typical fit: search across CAD and PLM records with an LLM front end.
Integration work with industrial systems such as SCADA, CAD, and PLM. Minimum engagement starts at $10,000+ (Clutch). Works best with clients in Manufacturing, Energy, Logistics, Retail & e-commerce.
Decision matrix: Quantiphi vs Addepto
| 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 Addepto ($10,000+ (Clutch)) |
| 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 Addepto
| Use case | Quantiphi fit | Addepto fit | Winner |
|---|---|---|---|
| Claims and medical-record extraction for insurers | Strong | Limited | Quantiphi |
| Contact-center assistants on Google Cloud | Strong | Limited | Quantiphi |
| Search across CAD and PLM records with an LLM front end | Limited | Strong | Addepto |
| Predictive maintenance from SCADA sensor history | Limited | Strong | Addepto |
Verdict: Quantiphi vs Addepto
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.
Addepto (4.3/5) is worth a look if you need predictive maintenance from SCADA sensor history. If your situation matches that, Addepto is a competitive option.
Related comparisons
Quantiphi vs Addepto FAQ
Is Quantiphi better than Addepto?
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. Addepto's strongest advantage: the $10K Clutch minimum lets small teams test an integration without a large commitment.
How do Quantiphi and Addepto differ in pricing?
Quantiphi's pricing: fixed-scope projects, time & materials, and dedicated teams; rates on request. Addepto's pricing: fixed-scope projects and time & materials; $50–$99/hr (Clutch band) with a minimum engagement of $10,000+ (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 Addepto?
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 Addepto?
Quantiphi's primary differentiator is: partner-of-the-year history with both Google Cloud and AWS on AI work. Addepto's primary differentiator is: integration work with industrial systems such as SCADA, CAD, and PLM. They also differ in team size (3,500+ vs 50–249), minimum engagement (Not disclosed vs $10,000+ (Clutch)), and primary industries served (Healthcare, Insurance vs Manufacturing, Energy).
Verify all details directly with each provider before making a decision.