Provectus vs Addepto: full comparison for 2026
Quick verdict
Provectus (4.6/5) edges ahead of Addepto (4.2/5) overall. Provectus is the better choice for AWS shops taking GenAI pilots to production. Addepto is the stronger option for mid-size firms wanting tested LLM apps cheaply. The right choice depends on how far your pilot has got, your budget, and who will run the system after launch.
Provectus vs Addepto: head-to-head summary
| Criterion | Provectus | Addepto |
|---|---|---|
| Founded | 2010 | 2017 |
| HQ | Palo Alto, USA | Warsaw, Poland |
| Team size | 570+ | 50–249 |
| Rating | 4.6 / 5 | 4.2 / 5 |
| Primary differentiator | AWS Premier Tier MLOps and generative AI engineering on Bedrock and SageMaker | Open-source LLM testing (ContextCheck) and a low $10,000+ Clutch entry point |
| Pricing model | Project and team pricing; $50–$99/hr (Clutch band) | Project-based; $50–$99/hr (Clutch band) |
| Min. engagement | $25,000+ (Clutch) | $10,000+ (Clutch) |
| Primary tech stack | AWS, Amazon Bedrock, Amazon SageMaker | Databricks, Azure, AWS |
| Industries served | Healthcare, Financial services, Retail, Media, Manufacturing | Manufacturing, Aviation, Logistics, Retail, Financial services |
Provectus vs Addepto: overview
Provectus
Provectus was founded in 2010 and is based in Palo Alto, California, with about 570 people according to Built In. It is an AWS Premier Tier partner and gained the AWS Generative AI Competency in March 2024, and its job postings describe it as an official Anthropic partner (per company job postings; independently unverifiable). Most of its work is MLOps and data platforms on AWS. If your pilot already runs on Amazon Bedrock or SageMaker and needs production plumbing around it, Provectus is a natural first call. Clutch lists $50–$99 an hour and a $25,000+ minimum project.
Addepto
Addepto was founded in Warsaw in 2017 and was acquired in December 2025 by KMS Technology, an Atlanta engineering company backed by Sunstone Partners. It built ContextCheck, an open-source framework for testing language models and chatbots, which says something about how it approaches quality before release. Its chief executive says 97% of staff are AI engineers (per company website; independently unverifiable). Clutch lists $50–$99 an hour and a $10,000+ minimum project.
Services and capabilities: Provectus vs Addepto
| Capability | Provectus | Addepto |
|---|---|---|
| LLM gateway & model routing | ✗ | ✗ |
| Regression tests on prompt and model changes | ✗ | ✓ |
| Canary or staged rollout | ✗ | ✗ |
| Hallucination and drift monitoring | ✓ | ✗ |
| MLOps & model serving | ✓ | ✓ |
| Fixed-scope pilot | ✗ | ✗ |
| Managed run after launch | ✓ | ✗ |
Tech stack comparison: Provectus vs Addepto
| Framework / platform | Provectus | Addepto |
|---|---|---|
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | N/A | N/A |
| Kubernetes | ✓ | N/A |
| MLflow | ✓ | N/A |
| Databricks | ✓ | ✓ |
| Amazon Bedrock | ✓ | N/A |
| Vertex AI | N/A | N/A |
| LangChain | N/A | ✓ |
| Snowflake | N/A | N/A |
Pricing comparison: Provectus vs Addepto
| Criterion | Provectus | Addepto |
|---|---|---|
| Minimum engagement | $25,000+ (Clutch) | $10,000+ (Clutch) |
| Engagement models | Fixed-scope project, Dedicated team, Managed services | Fixed-scope project, Time & materials, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Mid-market | Accessible |
Target audience comparison: Provectus vs Addepto
| Dimension | Provectus | Addepto |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthcare, Financial services, Retail | Manufacturing, Aviation, Logistics |
| Best use cases | Production MLOps for models running on SageMaker., Taking a Bedrock-based assistant from pilot to live service. | Testing a chatbot or LLM app before release., AI on manufacturing and aviation data. |
| Typical project type | Fixed-scope project | Fixed-scope project |
Provectus vs Addepto: pros and cons
| Provectus | |
|---|---|
| + | MLOps on AWS is its core business, built up over more than a decade |
| + | AWS Premier Tier and Generative AI Competency are checked by AWS itself |
| + | Data platform work and model serving come from one team |
| + | Published Clutch rates make budgeting easier |
| - | Strongly tied to AWS, so Azure or Google Cloud projects are a weaker fit |
| - | Mid-size team for very large multi-country programs |
| - | Little change-management or business-process work |
| Addepto | |
|---|---|
| + | ContextCheck shows real investment in testing language models |
| + | A $10,000+ Clutch minimum makes a small first project possible |
| + | Databricks experience for data-heavy builds |
| + | Team is almost all engineers |
| - | Acquired by KMS Technology in December 2025, so teams and priorities may change |
| - | No managed-run service listed |
| - | Less depth on staged rollouts than the leaders |
Who should choose Provectus?
A typical fit: production MLOps for models running on SageMaker.
AWS Premier Tier MLOps and generative AI engineering on Bedrock and SageMaker. Minimum engagement starts at $25,000+ (Clutch). Works best with clients in Healthcare, Financial services, Retail, Media, Manufacturing.
Who should choose Addepto?
A typical fit: testing a chatbot or LLM app before release.
Open-source LLM testing (ContextCheck) and a low $10,000+ Clutch entry point. Minimum engagement starts at $10,000+ (Clutch). Works best with clients in Manufacturing, Aviation, Logistics, Retail, Financial services.
Decision matrix: Provectus vs Addepto
| Your situation | Recommended choice |
|---|---|
| Your pilot works but nobody trusts it in production yet | Ask each for its release and rollback process |
| Model API spend is growing faster than usage | Neither lists a gateway; ask how cost per feature is tracked |
| You need someone to watch quality after launch | Provectus |
| You run classic ML models that need serving and retraining | Both cover MLOps |
| You want a priced pilot before a full rollout | Neither advertises one; ask for a scoped quote |
| Your budget is at the lower end | Addepto |
| You need a large team for many products at once | Provectus |
Use case fit: Provectus vs Addepto
| Use case | Provectus fit | Addepto fit | Winner |
|---|---|---|---|
| Production MLOps for models running on SageMaker. | Strong | Limited | Provectus |
| Taking a Bedrock-based assistant from pilot to live service. | Strong | Limited | Provectus |
| Testing a chatbot or LLM app before release. | Limited | Strong | Addepto |
| AI on manufacturing and aviation data. | Limited | Strong | Addepto |
Verdict: Provectus vs Addepto
Provectus (4.6/5) is the stronger overall choice for most AI Implementation projects. AWS Premier Tier MLOps and generative AI engineering on Bedrock and SageMaker.
Addepto (4.2/5) is worth a look if you need AI on manufacturing and aviation data. If your situation matches that, Addepto is a competitive option.
Related comparisons
Provectus vs Addepto FAQ
Is Provectus better than Addepto?
Provectus (4.6/5) scores higher overall, but "better" depends on your use case. Provectus's strongest advantage: MLOps on AWS is its core business, built up over more than a decade. Addepto's strongest advantage: ContextCheck shows real investment in testing language models.
How do Provectus and Addepto differ in pricing?
Provectus's pricing: project and team pricing; $50–$99/hr (Clutch band) with a minimum engagement of $25,000+ (Clutch). Addepto's pricing: project-based; $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: Provectus or Addepto?
Provectus 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 Provectus and Addepto?
Provectus's primary differentiator is: AWS Premier Tier MLOps and generative AI engineering on Bedrock and SageMaker. Addepto's primary differentiator is: open-source LLM testing (ContextCheck) and a low $10,000+ Clutch entry point. They also differ in team size (570+ vs 50–249), minimum engagement ($25,000+ (Clutch) vs $10,000+ (Clutch)), and primary industries served (Healthcare, Financial services vs Manufacturing, Aviation).
Verify all details directly with each provider before making a decision.