AI Automation Consulting
AI Automation That Ships in Weeks, Delivers ROI at Scale
We help enterprise teams turn manual work into measurable ROI — from AI strategy to production-grade deployment in weeks, not years.
Claims Automation Workflow
Document Intake & Ingestion
AI Extraction & Classification
Smart Routing & Decisioning
Compliance Check & Audit Trail
Processing: 94% straight-through rate
Years in enterprise AI
Engagements delivered
Weeks
U.S.
Extraordinary Results for Our Clients
Extraordinary Results for Our Clients
What It Is
What Is AI Automation Consulting?
AI automation consulting is the practice of identifying, designing, and deploying AI-powered workflows that reduce manual effort, accelerate decisions, and integrate intelligence into your existing business systems. Where rule-based RPA mimics human actions to automate repetitive tasks, AI automation intelligently handles workflows that previously required human judgment.
A qualified AI automation consultant doesn’t just wire up tools. They audit processes, identify AI leverage points, build and deploy production-grade systems, and stay accountable for outcomes after launch. The difference between a proof of concept and a production system lies in the engagement model — most projects stall right there. The right partner builds automation that runs inside your existing stack, against your real data, with a handoff your team can actually own.
Quick Comparison
RPA
Repetitive, rule-based tasks — clicks, copy-paste, form fills. Requires consistent, predictable inputs.
AI Automation
Ambiguous inputs, natural language, unstructured data. Handles exceptions and judgment-adjacent decisions.
Hyperautomation
Enterprise-wide orchestration — RPA + AI + process mining + analytics + governance coordinated across systems.
The Hard Truth
Why Most AI Projects Stall Before They Ship
Technology isn’t the deciding factor. What happens before and after the build decides the fate of the initiative.
01
No Use-Case Prioritization
Teams pick what’s technically interesting instead of what creates real business value.
02
Data Not Production-Ready
Most enterprise data has quality issues that surface only after the build starts — expensive to fix mid-project.
03
Tools Picked Before Problems Are Scoped
Buying a platform before scoping the problem forces your use case to fit the tool’s strengths.
04
No Change Management
A working AI system that no one adopts is a failed project. Change management must be built in from day one.
05
No Measurement Framework
Without predefined success metrics and a baseline, you can’t prove ROI or justify expansion.
06
Security & Governance Gaps
Speed without safeguards creates regulatory and operational risk — especially in Finance, Insurance, and Healthcare.
What We Build
AI Automation Services Across the Full Stack
From diagnostic to deployment to ongoing managed support — a full-stack engagement model built for production.
01
AI Readiness Assessment
A 2–4 week diagnostic: map your top automation opportunities, score use cases by ROI and feasibility, and get a prioritized AI roadmap.
02
Generative AI & LLM Solutions
Custom chatbots, RAG systems, and document Q&A — built on OpenAI, Anthropic, Gemini, and Bedrock, integrated with your internal systems.
03
Intelligent Document Processing
AI extraction from PDFs, contracts, claims, and invoices — replacing manual review with structured, auditable outputs.
04
AI Workflow Automation
End-to-end workflow automation integrated with Salesforce, Snowflake, AWS, and your existing stack — production systems, not isolated pilots.
05
Predictive Analytics & MLOps
Forecasting models, scoring engines, and monitoring pipelines — with MLOps infrastructure to track drift and retrain on schedule.
06
AI Agents & Autonomous Workflows
Multi-step AI agents that research, decide, and act across systems — with guardrails, audit trails, and human-in-the-loop checkpoints.
Industry Playbooks
AI Automation Use Cases by Industry
Common, high-value automation patterns we deploy across regulated and operations-heavy industries.
Financial Services
- Automated loan underwriting & credit risk scoring
- AI-assisted compliance monitoring & audit-trail generation
- Intelligent document processing for KYC / onboarding
- Real-time fraud detection and transaction flagging
- Automated reporting and regulatory filing preparation
client outcome
80%
Sales growth driven by AI-enabled pipeline and customer-intelligence tooling — Financial Services client
Insurance
- First-notice-of-loss automation and claims triage
- Intelligent document extraction from medical records & policies
- Automated subrogation detection and recovery
- AI-assisted underwriting and risk classification
- Fraud pattern detection and anomaly flagging
client outcome
40%
Increase in customer satisfaction (CSAT) after deploying AI-powered member support — HSA trustee client
Logistics
- Conversational AI for mobile field sales and dispatch
- Automated freight document processing & exception handling
- Predictive ETAs and dynamic routing
- Demand forecasting and inventory optimization
- Warehouse operations monitoring and anomaly detection
client outcome
90%
Reduction in answer-retrieval time for field and dispatch teams via Conversational AI — Logistics & Transportation Client
Real Estate & Construction
- Automated lease abstraction and contract review
- AI-powered property valuation and comp analysis
- Intelligent document processing for title & closing
- Construction safety monitoring with computer vision
- Predictive maintenance scheduling for property portfolios
Our Methodology
The RTS Production Sprint
Built on 14+ years and 600+ engagements — five stages, one accountable team, production-grade delivery in 4–24 weeks.
01
Discover
Weeks 1–2
Process audit, data-readiness assessment, and use-case scoring to confirm what to build and why.
02
Validate
Weeks 2–4
Rapid prototypes and technical spikes to validate feasibility and approach before full build commitment.
03
Build
Weeks 4–12
Production-grade development — model training, integrations, testing, and QA against real data.
04
Integrate
Weeks 8–16
System integration, security review, UAT, and go-live. Monitored rollout with rollback capability.
05
Evolve
Weeks 12–24+
Continuous monitoring, drift detection, retraining cadence, adoption analytics, and quarterly business reviews.
“Every stage of the Production Sprint exists because we’ve seen what happens without it. Discover without Validate leads to expensive wrong turns. Build without Evolve leads to models that drift. The methodology is the lesson list from 600+ engagements compressed into a repeatable process.”
Alex Hogancamp — Director of AI, RTS Labs
Honest Counsel
When AI Automation Is the Wrong Answer
Good AI consulting means knowing when the answer is no — we’ll tell you when automation isn’t the right move yet.
Low-Volume Processes
If a task takes an hour a week manually, the build and maintenance cost will never generate a positive return.
Pure Judgment Calls
High-stakes decisions requiring nuanced ethical or relational reasoning shouldn’t be fully automated.
Hyperautomation
Enterprise-wide orchestration — RPA + AI + process mining + analytics + governance coordinated across systems.
Broken Upstream Processes
Automating a broken process makes it break faster. AI accelerates the problem, not the fix.
Unreliable Data
If the data feeding a model is inconsistent or wrong, the model will be too.
No Executive Sponsor
Without an executive owner, adoption fails — and we won’t take on a project set up to fail.
Honest Comparison
RTS Labs vs. In-House vs. Big-4
Every company in your revenue band is weighing the same three paths. Here’s an honest look at the trade-offs.
Real Outcomes
AI Automation, Shipped
Production systems running against real data — with results we can point to.
Logistics
Evergreen: Data Into Conversations
Evergreen’s field sales team was losing hours each week pulling inventory data from disconnected systems. RTS Labs deployed a conversational AI interface giving reps instant answers from mobile devices in the field.
Minutes to Seconds
data-retrieval time for field reps
Automotive
Suncoast: Faster Answers With AI
Suncoast technicians needed precise specs from a vast, unstructured documentation library. RTS Labs built a RAG chatbot delivering accurate technical answers in seconds from verified product and warranty documentation.
average response time · hundreds of inquiries resolved weekly
Legal
Preferred Legal: AI-Powered Drafting
Preferred Legal attorneys spent up to 90 minutes per case drafting demand letters. RTS Labs deployed an AI drafting system that scans case files, populates templates, and calculates damages — reviewers start from a draft that’s 90% complete.
document prep · 120 min → 10 min
Why RTS Labs
The Difference Is the Team
01
14+ Years, 600+ Engagements
We’ve been building production AI since before ‘AI strategy’ was a board agenda item. That history is pattern recognition you can’t fake.
02
Full-Stack, Not a Tool Shop
Strategy, data engineering, model development, integration, governance, and MLOps under one team, one engagement, one accountability chain.
03
U.S.-Based, Compliance-Aware
Our team works with U.S. regulatory frameworks — SOC 2, HIPAA, FINRA, and state-level AI regulation — baked into how we build, not bolted on after.
04
Outcome-Tied Engagements
We define success metrics before we start, track them through delivery, and report against them post-launch.
leadership
Jyot Singh
Founder & CEO
Founded RTS Labs 14+ years ago. Has led AI and data-engineering engagements across Finance, Logistics, Insurance, and Healthcare for mid-market and enterprise clients.
Alex Hogancamp
Director of AI
Leads AI strategy and LLM engineering at RTS. Designed the Production Sprint methodology and oversees model architecture, evaluation, and governance practices.
Sandhya Ramamurthy
Director of Data Engineering
Leads data platform and pipeline architecture. Specializes in making enterprise data production-ready for AI — the step most projects skip and most projects fail at.
Tech Stack
Platform-Agnostic, Deeply Credentialed
We work with the platforms your enterprise already uses.
AI & LLM Frameworks
Cloud Platforms
Data Platforms
CRM & Business Apps
Automation & Integration
MLOps & Observability
Original Research
Inside the RTS AI Lab
We don’t just consult — we test, benchmark, and publish. Original research your team can act on.
[ Benchmark ]
Testing Document Text Extraction Across 9 Models
We benchmarked nine document AI models across accuracy, latency, and cost — with real enterprise document types. Results informed our IDP stack decisions.
[ Analysis ]
Vibe-Coding Platforms: A Practical Analysis for Enterprise Teams
We evaluated five no-code AI development platforms for enterprise suitability — security posture, customization limits, and real integration complexity.
[ Industry ]
AI in Construction Safety: Computer Vision Use Cases
An applied research piece on how computer-vision models are deployed for real-time safety monitoring on commercial job sites.
After Go-Live
What Happens After We Ship
of AI project budgets are spent after deployment — not during the build.
Monitoring & Drift Detection
Automated alerts when model performance degrades in production.
Retraining Cadence
Scheduled retraining cycles to keep models accurate as your data evolves.
Adoption Analytics
Tracking actual usage and surfacing friction points for your team.
Quarterly Business Reviews
Outcome-vs-baseline reporting against the success metrics we defined before the build.
Optional Managed Support
Fully managed AI operations for teams who don’t want to run AI infrastructure in-house.
Client Voices
What Clients Actually Say
“RTS Labs has been an invaluable partner in our journey. Their expertise and ability to understand our vision allowed them to deliver innovative, AI-powered solutions that align perfectly with our goals. Their collaborative approach and commitment to excellence have transformed how we operate, driving efficiency and unlocking new opportunities. We couldn’t have asked for a better partner.”
Jason Herzog
Founder, Holon Health
“RTS Labs became an extension of our team, delivering AI solutions that transformed how we operate. Their understanding of our needs and collaborative approach unlocked opportunities we hadn’t imagined. Truly a game changer for our business.”
Gemma Brooks
COO, BlueOceanBrain (an HSI Company)
Common Questions
Frequently Asked Questions
What is AI automation consulting?
AI automation consulting is the practice of identifying, designing, and deploying AI-powered workflows that reduce manual effort, accelerate decisions, and integrate intelligence into existing systems. A consulting firm scopes which processes are worth automating, builds the models and integrations, and sees the system through to production with accountability for business outcomes.
How is AI automation different from RPA?
RPA handles structured, rule-based tasks — scripted software that mimics clicks and data entry. AI automation handles variability: it reads unstructured documents, understands natural language, classifies ambiguous inputs, and makes probabilistic decisions. The two complement each other — AI handles messy upstream work, RPA handles structured downstream execution.
How much does AI automation consulting cost?
An AI Readiness Assessment (2–4 weeks) is the lowest-cost entry point — it produces a prioritized roadmap and realistic budget estimate before any full build commitment. Full production engagements vary by scope and complexity. RTS Labs provides fixed-scope pricing where possible rather than open-ended T&M billing.
How long does AI automation take to deploy?
A focused use case — a document-processing workflow, RAG chatbot, or predictive scoring model — can reach production in weeks. Multi-system, enterprise-wide programs take longer. The Production Sprint structures delivery into five stages from Discovery through Evolve, with a working system in production by the end of the Build stage.
What if our data isn't clean or ready?
This is the most common situation, and it’s not a blocker. The AI Readiness Assessment explicitly surfaces data quality and access gaps. For some use cases we work with imperfect data through preprocessing; for others, a short data-remediation phase is the right first investment. We’ll tell you honestly which situation you’re in.
Can AI be integrated with our existing CRM, ERP, or other systems?
Yes, and this is where most automation value is captured. AI that runs in isolation creates parallel workflows teams ignore; AI integrated into your systems of record creates adoption by default. We have deep integration experience with Salesforce, Microsoft Dynamics, Snowflake, Databricks, and most major enterprise platforms.
What's the ROI of AI automation?
Document-processing automation shows clear returns quickly — measurable in hours saved per week, headcount redeployment, or error-rate reduction. Predictive models and sales AI often show ROI in revenue impact, which takes longer but tends to be larger. We define success metrics before any build starts and report against them post-launch.
What processes shouldn't be automated with AI?
Low-volume processes, pure judgment calls, broken upstream workflows, processes with unreliable data, and situations without executive sponsorship. If the expected build cost won’t generate a return, if a human needs to own the decision for legal or ethical reasons, or if the data foundation isn’t there, we’ll tell you on the first call.
How do you ensure responsible and ethical AI?
Governance is designed into how we build — not reviewed at the end. That means audit trails for every automated decision, human-in-the-loop checkpoints for high-stakes workflows, regular bias evaluation, and documentation that satisfies compliance review. Our AI Governance practice is available as a standalone service.
Why choose RTS Labs over a Big-4 or in-house build?
For the $100M–$4B revenue band, the Big-4 is designed for companies 5–10x your size. Building in-house is the right long-term answer if you have the budget to hire, onboard, and retain a full-stack AI team — but that’s 12–18 months just to reach first production. RTS Labs is the sweet spot: enterprise-grade AI without the Big-4 timeline or the hiring overhead.
Let's Talk
Ready to Move From Pilot to Production?
Talk to an AI expert at RTS Labs. We’ll scope your highest-value automation opportunities and give you a realistic timeline and budget.
- ✓ No long-term contract required to start
- ✓ Typical first conversation: 30 minutes
- ✓ U.S.-based team, regulated-industry experience
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