RTS Labs vs Azumo: full comparison for 2026
Quick verdict
RTS Labs (4.4/5) edges ahead of Azumo (4.0/5) overall. RTS Labs is the better choice for U.S. firms needing onshore-only delivery. 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.
RTS Labs vs Azumo: head-to-head summary
| Criterion | RTS Labs | Azumo |
|---|---|---|
| Founded | 2010 | 2016 |
| HQ | Richmond, VA, USA | San Francisco, CA, USA |
| Team size | 100+ | 80+ |
| Rating | 4.4 / 5 | 4.0 / 5 |
| Primary differentiator | All-U.S. engineering team and early MCP integration work | Latin American engineers working U.S. hours |
| Pricing model | Fixed-scope phases and time & materials; rates on request | Dedicated teams and time & materials; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Salesforce, Microsoft Dynamics 365, Snowflake | Azure OpenAI, AWS Bedrock, LangChain |
| Industries served | Logistics, Insurance, Legal, Financial services, Real estate, Healthcare | SaaS, Media, Healthcare, Financial services |
RTS Labs vs Azumo: overview
RTS Labs
RTS Labs has been building software since 2010 from Richmond, Virginia, and now positions itself as an applied-AI consultancy. Its 100-plus staff are all U.S.-based, which matters for clients that can't send data or system access offshore. The firm says it has shipped over 600 software and AI systems and that core implementations usually reach production in 8–12 weeks (per company website; independently unverifiable). It's also one of the few mid-size firms publicly building Model Context Protocol (MCP) server integrations for enterprise tools.
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: RTS Labs vs Azumo
| Capability | RTS Labs | 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: RTS Labs vs Azumo
| Framework / platform | RTS Labs | Azumo |
|---|---|---|
| Salesforce | ✓ | N/A |
| SAP | N/A | N/A |
| Microsoft Dynamics 365 | ✓ | N/A |
| HubSpot | N/A | N/A |
| Snowflake | ✓ | ✓ |
| Databricks | N/A | N/A |
| BigQuery | N/A | N/A |
| Azure OpenAI | ✓ | ✓ |
| AWS Bedrock | ✓ | ✓ |
| Zendesk | N/A | N/A |
Pricing comparison: RTS Labs vs Azumo
| Criterion | RTS Labs | Azumo |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed-scope project, Time & materials, Managed services | Dedicated team, Time & materials |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: RTS Labs vs Azumo
| Dimension | RTS Labs | Azumo |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Logistics, Insurance, Legal | SaaS, Media, Healthcare |
| Best use cases | Connecting an agent to a TMS (transportation management system) and ERP for freight exceptions, Building MCP servers so assistants can query internal tools | Adding a chat assistant to a SaaS product, Extending an in-house team with LLM engineers |
| Typical project type | Fixed-scope project | Dedicated team |
RTS Labs vs Azumo: pros and cons
| RTS Labs | |
|---|---|
| + | Every engineer is U.S.-based, which simplifies data-residency and security reviews. |
| + | MCP server work lets agents call internal tools through one standard interface. |
| + | Logistics and insurance case work ties AI into operational systems. |
| + | Offers ongoing support once a system is live. |
| - | Onshore-only staffing means higher rates than nearshore firms |
| - | Its published timelines vary between 90 days and 8–12 weeks depending on the page |
| - | No hyperscaler partner tier is prominent in its materials |
| 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 RTS Labs?
A typical fit: connecting an agent to a TMS (transportation management system) and ERP for freight exceptions.
All-U.S. engineering team and early MCP integration work. Minimum engagement is not publicly disclosed. Works best with clients in Logistics, Insurance, Legal, Financial services, Real estate, Healthcare.
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: RTS Labs 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 | RTS Labs |
| Your budget is at the lower end | Compare: RTS Labs (Not disclosed) vs Azumo (Not disclosed) |
| The AI has to read and write in your CRM or ERP | RTS Labs |
| You need multi-step agents acting across systems | RTS Labs |
| You need a large team for a multi-year program | RTS Labs |
Use case fit: RTS Labs vs Azumo
| Use case | RTS Labs fit | Azumo fit | Winner |
|---|---|---|---|
| Connecting an agent to a TMS (transportation management system) and ERP for freight exceptions | Strong | Limited | RTS Labs |
| Building MCP servers so assistants can query internal tools | Strong | Limited | RTS Labs |
| Adding a chat assistant to a SaaS product | Limited | Strong | Azumo |
| Extending an in-house team with LLM engineers | Limited | Strong | Azumo |
Verdict: RTS Labs vs Azumo
RTS Labs (4.4/5) is the stronger overall choice for most AI Integration Services projects. All-U.S. engineering team and early MCP integration 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.
Related comparisons
RTS Labs vs Azumo FAQ
Is RTS Labs better than Azumo?
RTS Labs (4.4/5) scores higher overall, but "better" depends on your use case. RTS Labs's strongest advantage: every engineer is U.S.-based, which simplifies data-residency and security reviews. Azumo's strongest advantage: full time-zone overlap with U.S. clients.
How do RTS Labs and Azumo differ in pricing?
RTS Labs's pricing: fixed-scope phases and time & materials; 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: RTS Labs or Azumo?
RTS Labs 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 RTS Labs and Azumo?
RTS Labs's primary differentiator is: All-U.S. engineering team and early MCP integration work. Azumo's primary differentiator is: latin American engineers working U.S. hours. They also differ in team size (100+ vs 80+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Logistics, Insurance vs SaaS, Media).
Verify all details directly with each provider before making a decision.