AI consulting services built for companies that don't have a data team yet.

Three structured engagements — strategy, architecture, and implementation — designed for mid-size companies in the $10M–$50M revenue range. Each one builds on the last, and each one delivers working results, not slide decks.

01

Data & AI Strategy Assessment

Where you are, where you need to be, and the fastest path between them

Most mid-size companies know they need to do something with data and AI — they just don't know what's realistic, what it costs, or where to start. That uncertainty is expensive. It leads to either paralysis (doing nothing while competitors pull ahead) or wasted money (hiring a data analyst with no infrastructure to support them).

Our strategy assessment eliminates that uncertainty in 2–3 weeks. We audit your current data landscape — every spreadsheet, CRM, ERP, point-of-sale system, and QuickBooks file. We map your competitive position. And we deliver a concrete, prioritized roadmap that tells you exactly what to build, in what order, and what return to expect.

This isn't a 90-page consulting deck. It's a working document your leadership team can actually use to make decisions.

⏲ 2–3 weeks
What you get
Current-State Data Audit
Complete inventory of your data sources, systems, quality gaps, and integration opportunities.
Competitive Gap Analysis
How your data and technology capabilities compare to competitors in your market segment.
AI Opportunity Map
Specific AI and ML applications identified across sales, operations, finance, and marketing.
Prioritized Roadmap
Sequenced implementation plan with dependencies, timelines, and resource requirements.
ROI Projections
Financial analysis and expected returns for the top 3 recommended AI initiatives.
Technology Recommendations
Specific tools, platforms, and architecture decisions with cost comparisons.
02

Platform Architecture & Build

The data infrastructure that makes everything else possible

AI doesn't work without infrastructure. You can't run predictive analytics when your data lives in 15 different spreadsheets, two CRMs, and someone's email inbox. Before any machine learning model can deliver value, you need clean data flowing through a reliable system.

We design and build your data platform on AWS — the same cloud infrastructure used by Netflix, Airbnb, and most Fortune 500 companies — sized and priced for your business. Data pipelines pull from your existing systems automatically. Dashboards give your team real-time visibility. And everything is documented so your team can maintain it.

The key difference: we build for your current size with architecture that scales. You're not paying for enterprise complexity you don't need, but you're also not building something you'll outgrow in 18 months.

⏲ 8–12 weeks
What you get
AWS Cloud Infrastructure
Production-grade cloud environment with security, monitoring, and cost optimization built in.
Automated Data Pipelines
ETL processes that pull data from your existing systems — CRM, ERP, POS, accounting — automatically.
Real-Time Dashboards
Executive and operational dashboards that show your business metrics as they happen, not last month.
Data Warehouse
A single source of truth that combines all your business data in one queryable, organized location.
System Integrations
Connections to QuickBooks, Salesforce, Shopify, HubSpot, and other tools your team already uses.
Security & Compliance
Encryption, access controls, audit logging, and compliance configuration for your industry requirements.
03

AI & Machine Learning Implementation

Custom AI systems built for your specific business problems

This is where your data starts making money. With clean infrastructure in place, we build AI and machine learning models tailored to your business — not generic tools, but systems trained on your data to solve your problems.

A distributor might need demand forecasting that accounts for their specific seasonal patterns and supplier lead times. A services company might need cash flow prediction that factors in their project pipeline and payment cycles. A retailer might need customer segmentation that drives personalized marketing.

We also integrate large language models (LLMs) like Claude and GPT into your operations — building AI agents that can handle customer inquiries, process documents, analyze contracts, or automate reporting workflows. These aren't chatbots. They're operational tools that save your team hours every week.

⏲ 6–10 weeks per model
Common implementations
Predictive Analytics
Cash flow forecasting, demand prediction, customer churn analysis, and revenue projection models.
LLM & AI Agent Integration
Claude and GPT-powered agents for document processing, customer service, and operational automation.
Process Automation
ML-driven workflows that replace manual data entry, reporting, categorization, and quality checks.
Custom Model Training
Models trained on your proprietary business data for accuracy that generic tools can't match.
Price & Inventory Optimization
Dynamic pricing recommendations and inventory reorder points based on ML demand signals.
Monitoring & Optimization
Ongoing model performance tracking, retraining schedules, and accuracy improvement cycles.
Who This Is For

We work best with companies that fit this profile.

Not every company needs AI consulting. Here's who gets the most value from working with Veritas Data.

$10M–$50M in annual revenue

You've grown past the startup phase. You have real operational complexity, real data, and real decisions that could be improved with better analytics — but you haven't built the infrastructure to support it yet.

No internal data team (or a small one that's stuck)

You might have a data analyst or a technical person, but they're drowning in manual reporting and don't have the infrastructure, tools, or time to build anything strategic. Or you have no data function at all.

Ready to invest in data as a competitive advantage

You understand that data and AI are becoming the difference between companies that lead their markets and companies that struggle to keep up. You're looking for a partner who can get you there efficiently.

Common Questions

What clients typically ask before getting started.

What if we don't have clean data or any data infrastructure?
That's the most common starting point for our clients. Most come to us with data scattered across spreadsheets, QuickBooks, Shopify, various CRMs, and email. The strategy assessment maps everything you have, and the platform build creates the infrastructure from scratch. You don't need anything in place before we start.
How much does this cost compared to hiring a data team?
A full-time data scientist costs $200K+, an ML engineer $180K+, and cloud infrastructure runs $150K+ annually — that's $530K before they've built anything. Our structured engagements deliver the same capability at roughly 1/10th the cost over the first year. And you get working systems, not a team still figuring out your data.
Do we have to do all three engagements?
No. Most clients start with the strategy assessment to get clarity on what's possible and what it's worth. From there, you can decide whether to proceed with the platform build and AI implementation. Each engagement stands on its own and delivers independent value.
What happens after the engagement ends?
Everything we build is yours — the infrastructure, the models, the documentation. We train your team to maintain and operate the systems. We also offer ongoing support retainers for companies that want continued optimization, model retraining, and strategic guidance. The goal is your independence, not our dependency.
How is this different from hiring a big consulting firm?
Two ways. First, we build — most big firms deliver strategy decks and leave implementation to you. We deliver working systems. Second, we're sized for you — a $50K strategy engagement from Deloitte gives you a junior team using generic frameworks. Our assessments are led by a senior practitioner who's built these systems inside companies like yours.
Next Step

Start with a 45-minute discovery call. No cost, no pitch.

We'll talk about where your business is, what your competitors are doing with data and AI, and whether there's a fit. If there is, we'll outline what an engagement looks like. If there isn't, we'll tell you that too.

Schedule a Discovery Call