RTS Labs vs ScienceSoft: full comparison for 2026
Quick verdict
RTS Labs (4.2/5) edges ahead of ScienceSoft (4.0/5) overall. RTS Labs is the better choice for U.S. mid-market firms with stalled AI pilots. ScienceSoft is the stronger option for healthcare and finance firms wanting one IT vendor. The right choice depends on your project size, budget, and required tech stack.
RTS Labs vs ScienceSoft: head-to-head summary
| Criterion | RTS Labs | ScienceSoft |
|---|---|---|
| Founded | 2010 | 1989 |
| HQ | Glen Allen, VA, USA | McKinney, TX, USA |
| Team size | 51–200 | 750+ |
| Rating | 4.2 / 5 | 4.0 / 5 |
| Primary differentiator | Onshore U.S. team focused on getting a stalled pilot into production with ERP and CRM connections | Long-established generalist covering both the surrounding software and the AI feature |
| Pricing model | Fixed-scope assessments and builds, then T&M; rates on request | Fixed-price and T&M; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Salesforce, Snowflake, Azure OpenAI | Microsoft Dynamics 365, Salesforce, Azure OpenAI |
| Industries served | Logistics, Financial services, Healthcare, Manufacturing | Healthcare, Financial services, Retail, Manufacturing |
RTS Labs vs ScienceSoft: overview
RTS Labs
RTS Labs is a U.S. software and data consultancy founded in 2010, headquartered in Glen Allen, Virginia, near Richmond. It began with custom software, Salesforce implementation and business intelligence, and now positions itself as an implementation partner that takes AI and data systems from pilot to production. It says it has more than 100 senior engineers and AI architects and deploys in 8–12 weeks (per company website; independently unverifiable). Third-party estimates put headcount at 51–100.
ScienceSoft
ScienceSoft is an IT consulting and software development company founded in 1989, headquartered in McKinney, Texas, with more than 750 staff. It describes itself as an AI and software development firm, and its work spans healthcare IT, financial software, data analytics and machine learning integration. The company cites a 4.8 Clutch rating on its own pages. It is a generalist that covers AI as one service line among many.
Services and capabilities: RTS Labs vs ScienceSoft
| Capability | RTS Labs | ScienceSoft |
|---|---|---|
| CRM / ERP integration | ✓ | ✓ |
| LLM API gateway & cost control | ✗ | ✗ |
| Document processing | ✗ | ✓ |
| Agentic workflows | ✓ | ✗ |
| Fixed-price pilot | ✗ | ✗ |
| Managed services after launch | ✗ | ✗ |
| PII masking & access control | ✗ | ✗ |
Tech stack comparison: RTS Labs vs ScienceSoft
| Framework / platform | RTS Labs | ScienceSoft |
|---|---|---|
| Salesforce | ✓ | ✓ |
| SAP | N/A | N/A |
| Microsoft Dynamics 365 | N/A | ✓ |
| HubSpot | N/A | N/A |
| Snowflake | ✓ | N/A |
| Databricks | N/A | N/A |
| Azure OpenAI | ✓ | ✓ |
| AWS Bedrock | ✓ | N/A |
| LangChain | N/A | N/A |
| ServiceNow | N/A | N/A |
Pricing comparison: RTS Labs vs ScienceSoft
| Criterion | RTS Labs | ScienceSoft |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed project, Time & materials | Fixed project, Time & materials, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: RTS Labs vs ScienceSoft
| Dimension | RTS Labs | ScienceSoft |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Logistics, Financial services, Healthcare | Healthcare, Financial services, Retail |
| Best use cases | Connecting an AI agent to ERP order data for a logistics company., Rescuing a stalled proof of concept and putting it into production. | Adding AI document intake to a healthcare application., Analytics dashboards with predictive models for a lender. |
| Typical project type | Fixed project | Fixed project |
RTS Labs vs ScienceSoft: pros and cons
| RTS Labs | |
|---|---|
| + | Onshore U.S. delivery suits buyers who need data to stay with domestic staff |
| + | Salesforce implementation history helps when the CRM is part of the build |
| + | Explicit focus on production readiness, monitoring and fine-tuning after launch |
| + | Mid-market size keeps engagement minimums modest |
| - | Deployment-time and client-count claims are self-reported |
| - | Glassdoor employee reviews average about 3.0, which may point to retention issues |
| - | Smaller bench than national consultancies |
| ScienceSoft | |
|---|---|
| + | Three decades of operation suggests stability |
| + | Healthcare and finance domain knowledge |
| + | Can cover integration, testing and support under one contract |
| - | AI is one practice among many, with less specialist depth |
| - | Content-heavy marketing makes independent comparison harder |
Who should choose RTS Labs?
A typical fit: connecting an AI agent to ERP order data for a logistics company.
Onshore U.S. team focused on getting a stalled pilot into production with ERP and CRM connections. Minimum engagement is not publicly disclosed. Works best with clients in Logistics, Financial services, Healthcare, Manufacturing.
Who should choose ScienceSoft?
A typical fit: adding AI document intake to a healthcare application.
Long-established generalist covering both the surrounding software and the AI feature. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Financial services, Retail, Manufacturing.
Decision matrix: RTS Labs vs ScienceSoft
| Your situation | Recommended choice |
|---|---|
| You want a fixed-price audit or pilot before committing | Neither advertises one; ask for a scoped pilot |
| AI has to work inside your existing CRM or ERP | Both |
| Personal data must be masked and answers limited by user permissions | Ask both for their PII and access-control design |
| Your budget is at the lower end | Compare: RTS Labs (Not disclosed) vs ScienceSoft (Not disclosed) |
| You want the vendor to run the AI service after launch | Neither offers managed services; plan in-house operations |
| You are building multi-step agents across systems | RTS Labs |
Use case fit: RTS Labs vs ScienceSoft
| Use case | RTS Labs fit | ScienceSoft fit | Winner |
|---|---|---|---|
| Connecting an AI agent to ERP order data for a logistics company. | Strong | Limited | RTS Labs |
| Rescuing a stalled proof of concept and putting it into production. | Strong | Limited | RTS Labs |
| Adding AI document intake to a healthcare application. | Limited | Strong | ScienceSoft |
| Analytics dashboards with predictive models for a lender. | Limited | Strong | ScienceSoft |
Verdict: RTS Labs vs ScienceSoft
RTS Labs (4.2/5) is the stronger overall choice for most AI Integration projects. Onshore U.S. team focused on getting a stalled pilot into production with ERP and CRM connections.
ScienceSoft (4.0/5) is worth a look if you need analytics dashboards with predictive models for a lender. If your situation matches that, ScienceSoft is a competitive option.
Related comparisons
RTS Labs vs ScienceSoft FAQ
Is RTS Labs better than ScienceSoft?
RTS Labs (4.2/5) scores higher overall, but "better" depends on your use case. RTS Labs's strongest advantage: onshore U.S. delivery suits buyers who need data to stay with domestic staff. ScienceSoft's strongest advantage: three decades of operation suggests stability.
How do RTS Labs and ScienceSoft differ in pricing?
RTS Labs pricing: Fixed-scope assessments and builds, then T&M; rates on request. ScienceSoft pricing: Fixed-price and T&M; rates on request. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: RTS Labs or ScienceSoft?
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 company before shortlisting.
What are the main differences between RTS Labs and ScienceSoft?
RTS Labs's primary differentiator is: onshore U.S. team focused on getting a stalled pilot into production with ERP and CRM connections. ScienceSoft's primary differentiator is: long-established generalist covering both the surrounding software and the AI feature. They also differ in team size (51–200 vs 750+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Logistics, Financial services vs Healthcare, Financial services).
Verify all details directly with each company before making a decision.