Best Machine Learning Agencies

RTS Labs

Virginia-based AI and ML consultancy taking data engineering projects from pilot to production since 2010.

Founded 2010 | Richmond, VA | 50–150 employees
ml-consultingdata-engineeringpredictive-analyticscustom-ml-buildmlops

What is RTS Labs?

RTS Labs was founded in 2010 and is headquartered in Richmond, Virginia. The firm specialises in AI and ML projects from pilot to production, with strong roots in data engineering — pipelines, warehousing, and integration. Core platforms include Azure, AWS, Salesforce, and Snowflake, with ML applied to financial services, healthcare, and manufacturing use cases. RTS Labs has been ranked a top ML consulting firm for mid-sized US businesses. (Founding year and specialisation per RTS Labs official website.)

RTS Labs was founded in 2010 and is headquartered in Richmond, VA. The firm employs 50–150 people and works primarily with clients in financial, healthcare, manufacturing, logistics, saas sectors. Its primary differentiator is: Pilot-to-production ML with deep data engineering roots — Snowflake, Azure, and AWS native.

RTS Labs tech stack and services

PythonAzureAWSSnowflakeSalesforcescikit-learnPower BIdbt
Service area
ML Consulting
Data Engineering
Predictive Analytics
Custom ML Build
MLOps

RTS Labs use cases

Short answer: RTS Labs is best suited for US finance/healthcare firms, pilot-to-production AI.

Use case
ML-powered financial fraud detection
Healthcare data pipeline and predictive analytics
Snowflake data warehouse with ML layer
Salesforce CRM with ML scoring
Manufacturing defect prediction model

RTS Labs pricing

Short answer: RTS Labs uses a fixed project, t&m pricing approach. Minimum engagement starts at $20K+.

Engagement model Typical range Best for
Fixed project From $20K+ Well-defined scope
T&M Variable; depends on team size Large programmes or team augmentation
RTS Labs does not publish a public rate card. Contact them directly via their website to get project-specific pricing.

RTS Labs pros and cons

Advantages Things to consider
+Pilot-to-production ML ownership — not just consulting deliverables -Smaller team limits concurrent large programmes
+Strong data engineering base: pipelines, warehousing, Snowflake, dbt -Less international delivery footprint than larger firms
+Azure and AWS native with Salesforce integration experience
+US-based with financial services and healthcare domain knowledge
+Practical, outcome-focused approach for mid-market budgets

RTS Labs vs alternatives

How RTS Labs compares to the other top Machine Learning agencies.

Company Best for Key difference Rating Compare
Tensorway Mid-market teams, full-lifecycle ML ownership. Full-lifecycle ML ownership — model design, training infrastructure, and drift monitoring in one team 4.8 Full comparison
InData Labs Fintech, healthcare, SaaS — production ML with GenAI/RAG. Deep ML and GenAI specialist with 10+ years of production deployments across regulated industries 4.6 Full comparison
Artefact Large enterprises, industrial-scale ML and data strategy. Enterprise ML at 1,500-consultant scale across 26 countries — strategy, deployment, and AI factory in one firm 4.5 Full comparison
N-iX Enterprise teams, ML plus cloud engineering, European delivery. 2,400+ engineers covering ML, cloud, and data under one firm — strong for large multi-track programmes 4.4 Full comparison
Sigmoid Fortune 500 retail/CPG/financial firms, AI-first data platforms. Sequoia-backed AI and data engineering specialist with a Fortune 500 client portfolio in retail and CPG 4.3 Full comparison
Scopic Healthcare, fintech enterprises — genuinely custom ML. 20-year track record of custom ML engineering across 1,000+ projects — no API-wrapper shortcuts 4.2 Full comparison
Miquido Product companies, ML embedded in mobile/web products. AI-plus-product development — ML capabilities integrated with UX engineering, not delivered as a standalone model 4.2 Full comparison
NineTwoThree AI Studio Mid-market scale-ups, boutique AI/ML studio. Inc. 5000 AI studio with Clutch Top 50 ranking — boutique delivery model with direct principal access 4.1 Full comparison
SciForce Production NLP/CV systems, cost-effective Eastern Europe. End-to-end ML delivery — from requirements to post-launch support — with NLP and computer vision depth 4.0 Full comparison
LeewayHertz Enterprise clients, AI engineering, Hackett-backed. Backed by The Hackett Group since Sept 2024 — AI engineering within an enterprise transformation consulting firm 4.0 Full comparison
DATAFOREST US/EU companies, affordable AI, verified Clutch ratings. 4.9-star Clutch rating across 27 verified reviews — one of the highest-rated AI firms in Eastern Europe 4.0 Full comparison
Kanerika US enterprises, AI strategy plus data engineering. Enterprise data-to-value specialist — ML consulting plus data integration and process automation in one engagement 4.0 Full comparison
DataArt Enterprises, established firm, fintech/travel ML depth. 1997-founded, 5,700-engineer global firm — enterprise scale and continuity across ML and software in fintech and travel 3.9 Full comparison
ELEKS Enterprise clients, ML within full-service consulting. 30+ years of enterprise software delivery — ML within a stable, large-org structure for risk-averse buyers 3.9 Full comparison
Yalantis Healthcare, fintech — compliance-aware ML plus IoT. Compliance-first ML delivery — particularly strong for healthcare and regulated fintech with IoT integration needs 3.9 Full comparison
Avenga European enterprises, large-scale ML transformation. Formed from a 2019 merger — 3,800+ engineers across Europe for large ML and digital transformation programmes 3.9 Full comparison
Intellectsoft Fortune 500, AI modernisation of legacy systems. AI modernisation specialist for Fortune 500 mission-critical systems — legacy transformation, not greenfield 3.8 Full comparison
Azumo US companies, cost-effective Latin American nearshore ML. Latin American nearshore delivery — US time-zone alignment with rates below fully on-shore alternatives 3.8 Full comparison
Iflexion Enterprises, ML within software modernisation. 25 years of software delivery with ML integrated — 800+ clients provide a verified delivery track record 3.8 Full comparison
Altamira Companies, production-ready AI agents from day one. AI-native product-build firm — delivers fully integrated, trained AI agents ready for production from day one 3.8 Full comparison
Maruti Techlabs Mid-market companies, cost-effective US/India ML delivery. Dual US-India delivery with AWS Marketplace listing — cost-effective ML for mid-market budgets 3.8 Full comparison
Keyrus International enterprises, industrial-AI implementation. From experimental AI to industrial AI — consulting group specialising in productionising ML for large organisations 3.8 Full comparison
Itransition Global enterprises, ML within full software delivery. 25+ years of full-cycle delivery to 30+ countries — ML within a large proven software engineering organisation 3.8 Full comparison
Turing Companies needing rapid, vetted ML staff augmentation. AI-vetted 4M+ developer network — fastest route to pre-screened ML talent for staff augmentation 3.8 Full comparison
Acropolium SaaS startups, ML features in custom product builds. 22 years of bespoke product engineering — ML as a product feature, not a standalone model delivery 3.8 Full comparison
Kanda Software Healthcare, pharma — compliance-aware AI development. Regulatory-domain ML specialist — AI for pharma and healthcare with compliance and IP ownership built in 3.7 Full comparison
Binariks Companies, cost-effective ML with cloud/IoT integration. Multi-cloud and IoT-integrated ML delivery — AWS, GCP, and Azure with IoT sensor data pipelines 3.7 Full comparison
Centric Consulting US enterprises, ML within business transformation. Business-outcome ML consulting — AI within management transformation, not pure technology delivery 3.7 Full comparison
Space-O Technologies Startups/SMBs, accessible ML in healthcare/e-commerce. Budget-accessible ML for startups — low minimum engagement with India-based rate advantage 3.7 Full comparison
Modak Large enterprises, AI-driven data modernisation. ML-powered data engineering — uses ML itself to accelerate data prep and modernisation at enterprise scale 3.7 Full comparison

RTS Labs FAQ

What is RTS Labs?

RTS Labs was founded in 2010 and is headquartered in Richmond, Virginia. The firm specialises in AI and ML projects from pilot to production, with strong roots in data engineering — pipelines, warehousing, and integration. Core platforms include Azure, AWS, Salesforce, and Snowflake, with ML applied to financial services, healthcare, and manufacturing use cases. RTS Labs has been ranked a top ML consulting firm for mid-sized US businesses. (Founding year and specialisation per RTS Labs official website.)

How much does RTS Labs charge?

RTS Labs uses fixed project, t&m pricing. Minimum engagement starts at $20K+. A discovery call is required to get project-specific quotes.

What tech stack does RTS Labs use?

RTS Labs works with Python, Azure, AWS, Snowflake, Salesforce, scikit-learn, Power BI, dbt. Primary industries served include financial, healthcare, manufacturing, logistics, saas.

Is RTS Labs right for enterprise?

US finance/healthcare firms, pilot-to-production AI. 50–150 team size. Key consideration: Smaller team limits concurrent large programmes.

What are the best RTS Labs alternatives?

The best alternatives to RTS Labs depend on your use case. Top options are:

  • Tensorway: full-lifecycle ml ownership — model design, training infrastructure, and drift monitoring in one team
  • InData Labs: deep ml and genai specialist with 10+ years of production deployments across regulated industries
  • Artefact: enterprise ml at 1,500-consultant scale across 26 countries — strategy, deployment, and ai factory in one firm
See full alternatives list

Compare RTS Labs with other Machine Learning agencies