Top AI Integration Services

RTS Labs vs Addepto: full comparison for 2026

Quick verdict

RTS Labs (4.4/5) edges ahead of Addepto (4.3/5) overall. RTS Labs is the better choice for U.S. firms needing onshore-only delivery. 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.

RTS Labs vs Addepto: head-to-head summary

Criterion RTS Labs Addepto
Founded 2010 2018
HQ Richmond, VA, USA Warsaw, Poland
Team size 100+ 50–249
Rating 4.4 / 5 4.3 / 5
Primary differentiator All-U.S. engineering team and early MCP integration work Integration work with industrial systems such as SCADA, CAD, and PLM
Pricing model Fixed-scope phases and time & materials; rates on request Fixed-scope projects and time & materials; $50–$99/hr (Clutch band)
Min. engagement Not disclosed $10,000+ (Clutch)
Primary tech stack Salesforce, Microsoft Dynamics 365, Snowflake Databricks, Azure OpenAI, Snowflake
Industries served Logistics, Insurance, Legal, Financial services, Real estate, Healthcare Manufacturing, Energy, Logistics, Retail & e-commerce

RTS Labs vs Addepto: 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.

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: RTS Labs vs Addepto

Capability RTS Labs 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: RTS Labs vs Addepto

Framework / platform RTS Labs Addepto
Salesforce ✓ N/A
SAP N/A N/A
Microsoft Dynamics 365 ✓ N/A
HubSpot N/A N/A
Snowflake ✓ ✓
Databricks N/A ✓
BigQuery N/A N/A
Azure OpenAI ✓ ✓
AWS Bedrock ✓ N/A
Zendesk N/A N/A

Pricing comparison: RTS Labs vs Addepto

Criterion RTS Labs Addepto
Minimum engagement Not disclosed $10,000+ (Clutch)
Engagement models Fixed-scope project, Time & materials, Managed services Fixed-scope project, Time & materials
Rate transparency Not public Minimum disclosed
Price tier Mid-market Accessible

Target audience comparison: RTS Labs vs Addepto

Dimension RTS Labs Addepto
Best company size Startup to mid-market Startup to mid-market
Best industries Logistics, Insurance, Legal Manufacturing, Energy, Logistics
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 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

RTS Labs vs Addepto: 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
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 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 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: RTS Labs 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 RTS Labs
Your budget is at the lower end Compare: RTS Labs (Not disclosed) vs Addepto ($10,000+ (Clutch))
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 Addepto

Use case RTS Labs fit Addepto 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
Search across CAD and PLM records with an LLM front end Limited Strong Addepto
Predictive maintenance from SCADA sensor history Limited Strong Addepto

Verdict: RTS Labs vs Addepto

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.

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

RTS Labs vs Addepto FAQ

Is RTS Labs better than Addepto?

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. Addepto's strongest advantage: the $10K Clutch minimum lets small teams test an integration without a large commitment.

How do RTS Labs and Addepto differ in pricing?

RTS Labs's pricing: fixed-scope phases and time & materials; 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: RTS Labs or Addepto?

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 Addepto?

RTS Labs's primary differentiator is: All-U.S. engineering team and early MCP integration work. Addepto's primary differentiator is: integration work with industrial systems such as SCADA, CAD, and PLM. They also differ in team size (100+ vs 50–249), minimum engagement (Not disclosed vs $10,000+ (Clutch)), and primary industries served (Logistics, Insurance vs Manufacturing, Energy).

Verify all details directly with each provider before making a decision.