AI & Machine Learning
Practical AI and machine learning for business operations
TrendLab Analytics builds practical AI and machine learning systems for small and mid-size businesses: demand and cash-flow forecasting, anomaly detection on claims, transactions and operations data, and large-language-model automation that reads, classifies and drafts documents and email. We are an Atlanta, Georgia AI consultancy serving clients nationwide, led by a principal consultant with 17 years in healthcare finance and analytics and a decade of Python. The focus is on models that ship into a workflow and get used, not slide-deck prototypes.
Who this is for
- •Finance and operations leaders who want forecasts and early warnings instead of month-end surprises
- •Teams drowning in inbound documents, forms or email that need to be sorted, extracted and routed
- •Companies with a few years of transaction, claims or usage data and no one mining it
What you get
- •Forecasting models for revenue, demand, cash flow or utilization, with clear accuracy reporting
- •Anomaly and fraud detection that flags unusual transactions, claims or metrics for review
- •LLM automation: document classification, data extraction from PDFs and email, first-draft replies and summaries
- •Automated data exploration: models and scripts that profile new data, find the segments and outliers that matter, and hand analysts a shortlist instead of a haystack
- •Deployment into your workflow (dashboard, email, spreadsheet or API) with monitoring
- •A plain-English explanation of what the model does, its limits, and how to keep it honest
Results from similar work
AI
driven signals in capital markets
Custom statistical models for market analysis, anomaly detection and algorithmic strategies with consistent data-driven results.
10,000+
documents handled by rules and models
Conditional-logic document generation at scale, the same foundation used for LLM-based document workflows.
How it works
- 1.Discovery call to define the decision the model supports and the data available
- 2.A short feasibility pass on your data before you commit to a build
- 3.Model development with a baseline first, so gains are measured against what you do today
- 4.Deployment, monitoring and a hand-off so results stay reliable
Timeline
A feasibility pass takes 1 to 2 weeks. A production model or LLM workflow usually ships in 4 to 8 weeks.
Pricing
The feasibility pass is a small fixed fee that tells you whether a build is worth it. Builds are fixed-scope quotes after that.
Tools
Python · scikit-learn · pandas and NumPy · Claude, OpenAI and Gemini APIs · Local LLMs (Ollama, llama.cpp) · SQL: Snowflake, BigQuery, Teradata, PostgreSQL · AWS · Prophet and statsmodels
AI & Machine Learning questions answered
Straight answers. If yours is not here, the discovery call is free.
Is my business too small for AI?
No. The best small-business AI projects are narrow: one forecast, one classification step, one document type. A feasibility pass tells you quickly whether your data supports it.
Can you use ChatGPT or Claude in our workflow?
Yes. We build automation on the Claude and OpenAI APIs to read, classify, extract and draft, with guardrails and human review where it matters, and with your data handled under your policies.
How do we know the model is right?
Every model is measured against a baseline and reported with plain-English accuracy numbers before it goes live, and monitored after.
How much does an AI project cost?
A feasibility pass is a small fixed fee. Production builds are quoted as a fixed scope after a free discovery call.
Do you also build AI agents?
Yes. Agents that plan and execute multi-step work across your tools, on cloud models or on local LLMs for privacy, are their own service: see Agentic AI and Context Engineering.
Where are you located?
Atlanta, Georgia, serving clients across the United States remotely.
Start with a free 30-minute call
Tell us the process, report or dataset that is costing you the most time. You leave with a clear next step, whether or not that is us.
Other services: Business Process Automation · Analytics & Dashboard Reporting · Data Engineering · Agentic AI & Context Engineering