Discovery & audit
Stack, data, workflows, and constraints. You leave with a readiness view and a short list of first systems worth building.
Data
Predictive Analytics & Data Intelligence
Turn historical noise into forward-looking decisions. Churn before it happens, demand before it spikes, risk before it costs you.
Predictive ModelingRAG SystemsDecision Intelligence
Initiate ProjectSee Around Corners
Every business generates data. Most drown in it. We build predictive analytics systems that transform historical data into forward-looking intelligence. So you can act before events happen, not after. Customer churn before it occurs. Demand spikes before they hit. Equipment failures before they cause downtime. Fraud before it drains your accounts. Our models don't just predict. They prescribe actions, quantify confidence levels, and integrate directly into your decision-making workflows.
RAG Knowledge Bases: Your Data, Instantly Queryable
Your company's collective knowledge lives in documents, wikis, Slack threads, emails, and databases. Scattered and unsearchable. We build Retrieval-Augmented Generation (RAG) systems that make all of it instantly queryable in natural language. Ask "What's our refund policy for enterprise clients?" or "Show me all deals lost to Competitor X in Q3" and get accurate, cited answers in seconds. RAG systems eliminate knowledge silos, accelerate onboarding, and give every team member access to institutional intelligence.
Decision Intelligence: From Dashboards to Direction
Dashboards tell you what happened. Decision intelligence tells you what to do. We build systems that go beyond reporting. They analyze situations, evaluate options, model outcomes, and recommend actions with quantified confidence. A pricing engine that recommends optimal price points by segment. An inventory system that suggests reorder quantities based on demand forecasts and supplier lead times. A customer success platform that flags at-risk accounts and prescribes intervention strategies. This is analytics that drives action, not just observation.
How we engageWeek 1–2 Week 2–3 Week 3–8 Optional, ongoing
Engagement model
The same four-phase path on every service lander. Scope and price are quoted after discovery. The bands below already appear on the site FAQ. We do not invent a new price list per page.
Strategy & roadmap
Phased plan, success metrics, and an ROI model for the first initiative. You approve scope before we write production code.
Build & deploy
One production system in your environment: integrations, evals, guardrails, and team training. First sprints often land in 2–6 weeks when the workflow is narrow.
Operate & optimize
Managed AI Operations if you want us to monitor, update models, and keep costs honest after go-live.
Focused projects$10K–$50K
Transformation programs$100K+
Managed AI OperationsFrom $3,000/month
Exact scope is quoted after a discovery call. No surprise invoices.
Initiate ProjectWhat You Get
- Data audit and pipeline architecture
- Custom predictive models (churn, demand, risk, fraud, LTV)
- RAG knowledge base with natural language search
- Decision intelligence dashboards with prescriptive recommendations
- Real-time alerting and automated action triggers
- Data warehouse and ETL pipeline setup
- Model monitoring, drift detection, and retraining pipelines
Expected Outcomes
- Churn and risk scores your account team can act on, with evals
- Demand and inventory signals connected to the tools ops already opens
- A RAG knowledge base that cites your documents, not a generic chatbot
- Recommendations with confidence scores, not another dashboard nobody uses
- Monitoring for drift so the model does not quietly decay
FAQ
Predictive Analytics: Common Questions
How much data do we need for predictive analytics?
It depends on the use case. Some models work with as few as 1,000 records. Others require months of historical data. Part of our engagement is assessing your data landscape and recommending what can be built now versus what requires additional data collection.
What is a RAG system and why do we need one?
RAG (Retrieval-Augmented Generation) combines a search engine with an AI language model over your private data. Instead of generic AI answers, you get responses grounded in your actual documents, policies, and data. With citations. It eliminates knowledge silos and makes institutional knowledge instantly accessible.
How do you ensure model accuracy and prevent drift?
We implement continuous monitoring with drift detection, automated retraining pipelines, and human-in-the-loop validation for high-stakes predictions. Models are evaluated against held-out test data and business outcomes, not just technical metrics.
Florida
Serving Florida with Predictive Analytics
Remote-first full-stack AI for Miami, Fort Lauderdale, Tampa Bay, and the South Florida corridor. One partner from roadmap to production ops. First sprints typically run 2-6 weeks.
Contact
Initiate a Project
Tell us what you're building: automation, marketing, software, or full-stack transformation. Florida operators in Miami, Fort Lauderdale, Tampa, and South Florida included. We respond within one business day.
Direct line[email protected]
Response time
Under 24 hours
Florida service area
Signal status
Accepting new engagements