Quantiphi vs RTS Labs: full comparison for 2026
Quick verdict
Quantiphi (4.3/5) edges ahead of RTS Labs (4.2/5) overall. Quantiphi is the better choice for google Cloud estates, high-volume document AI. RTS Labs is the stronger option for U.S. mid-market firms with stalled AI pilots. The right choice depends on your project size, budget, and required tech stack.
Quantiphi vs RTS Labs: head-to-head summary
| Criterion | Quantiphi | RTS Labs |
|---|---|---|
| Founded | 2013 | 2010 |
| HQ | Marlborough, MA, USA | Glen Allen, VA, USA |
| Team size | 3,500+ | 51–200 |
| Rating | 4.3 / 5 | 4.2 / 5 |
| Primary differentiator | Premier partner on both Google Cloud and AWS, with a long run of Document AI and contact-centre deployments | Onshore U.S. team focused on getting a stalled pilot into production with ERP and CRM connections |
| Pricing model | Fixed-price and T&M with offshore-weighted rates; rates on request | Fixed-scope assessments and builds, then T&M; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Google Vertex AI, Google Document AI, AWS Bedrock | Salesforce, Snowflake, Azure OpenAI |
| Industries served | Healthcare, Insurance, Financial services, Public sector, Media | Logistics, Financial services, Healthcare, Manufacturing |
Quantiphi vs RTS Labs: overview
Quantiphi
Quantiphi is an AI-first digital engineering firm founded in 2013, with U.S. headquarters in Marlborough, Massachusetts and most of its delivery staff in India. It employs about 3,500–4,000 people and holds premier-level partnerships with Google Cloud and AWS, plus many partner-of-the-year awards (exact counts differ across its own pages). Document AI, contact-centre AI and data modernization make up much of its published work.
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.
Services and capabilities: Quantiphi vs RTS Labs
| Capability | Quantiphi | RTS Labs |
|---|---|---|
| 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: Quantiphi vs RTS Labs
| Framework / platform | Quantiphi | RTS Labs |
|---|---|---|
| Salesforce | N/A | ✓ |
| SAP | N/A | N/A |
| Microsoft Dynamics 365 | N/A | N/A |
| HubSpot | N/A | N/A |
| Snowflake | ✓ | ✓ |
| Databricks | ✓ | N/A |
| Azure OpenAI | N/A | ✓ |
| AWS Bedrock | ✓ | ✓ |
| LangChain | N/A | N/A |
| ServiceNow | N/A | N/A |
Pricing comparison: Quantiphi vs RTS Labs
| Criterion | Quantiphi | RTS Labs |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed project, Time & materials, Dedicated team | Fixed project, Time & materials |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Quantiphi vs RTS Labs
| Dimension | Quantiphi | RTS Labs |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthcare, Insurance, Financial services | Logistics, Financial services, Healthcare |
| Best use cases | Insurance claims intake with Document AI extraction and human review., Contact-centre AI on Google Cloud for a high-volume support operation. | Connecting an AI agent to ERP order data for a logistics company., Rescuing a stalled proof of concept and putting it into production. |
| Typical project type | Fixed project | Fixed project |
Quantiphi vs RTS Labs: pros and cons
| Quantiphi | |
|---|---|
| + | Rare dual premier status with Google Cloud and AWS |
| + | Mature document AI practice for claims, forms and medical records |
| + | India-weighted delivery keeps blended rates below U.S. consultancies |
| + | Can scale teams quickly for large backlogs |
| - | Award and partner counts vary between its own pages, so confirm current tiers in partner directories |
| - | Offshore-heavy delivery needs strong client-side product ownership |
| - | Less visible work inside Salesforce or SAP |
| 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 |
Who should choose Quantiphi?
A typical fit: insurance claims intake with Document AI extraction and human review.
Premier partner on both Google Cloud and AWS, with a long run of Document AI and contact-centre deployments. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Insurance, Financial services, Public sector, Media.
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.
Decision matrix: Quantiphi vs RTS Labs
| 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 | RTS Labs |
| 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: Quantiphi (Not disclosed) vs RTS Labs (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: Quantiphi vs RTS Labs
| Use case | Quantiphi fit | RTS Labs fit | Winner |
|---|---|---|---|
| Insurance claims intake with Document AI extraction and human review. | Strong | Limited | Quantiphi |
| Contact-centre AI on Google Cloud for a high-volume support operation. | Strong | Limited | Quantiphi |
| Connecting an AI agent to ERP order data for a logistics company. | Limited | Strong | RTS Labs |
| Rescuing a stalled proof of concept and putting it into production. | Limited | Strong | RTS Labs |
Verdict: Quantiphi vs RTS Labs
Quantiphi (4.3/5) is the stronger overall choice for most AI Integration projects. Premier partner on both Google Cloud and AWS, with a long run of Document AI and contact-centre deployments.
RTS Labs (4.2/5) is worth a look if you need rescuing a stalled proof of concept and putting it into production. If your situation matches that, RTS Labs is a competitive option.
Related comparisons
Quantiphi vs RTS Labs FAQ
Is Quantiphi better than RTS Labs?
Quantiphi (4.3/5) scores higher overall, but "better" depends on your use case. Quantiphi's strongest advantage: rare dual premier status with Google Cloud and AWS. RTS Labs's strongest advantage: onshore U.S. delivery suits buyers who need data to stay with domestic staff.
How do Quantiphi and RTS Labs differ in pricing?
Quantiphi pricing: Fixed-price and T&M with offshore-weighted rates; rates on request. RTS Labs pricing: Fixed-scope assessments and builds, then 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: Quantiphi or RTS Labs?
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 Quantiphi and RTS Labs?
Quantiphi's primary differentiator is: premier partner on both Google Cloud and AWS, with a long run of Document AI and contact-centre deployments. RTS Labs's primary differentiator is: onshore U.S. team focused on getting a stalled pilot into production with ERP and CRM connections. They also differ in team size (3,500+ vs 51–200), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Healthcare, Insurance vs Logistics, Financial services).
Verify all details directly with each company before making a decision.