See how these capabilities become a field-ready support system for Real Estate Agents.
Finance, data, and AI systems for businesses scaling beyond what spreadsheets can hold.
AI is an unbelievable tool. It also needs the right context, the right scope, and the right hands.
We bring all three. The diagnosis of what’s actually worth automating. The discipline to keep the implementation small. The operator’s eye for whether the thing we built is going to survive contact with a real workday.
Augusta-based consulting for service-based businesses and operational SMBs that need senior finance, BI, and AI expertise without the full-time hire.
Most service businesses don’t have a data problem. They have a visibility problem.
The data exists. It’s trapped in seven different places: the field app, the billing system, the spreadsheet one person knows how to update, the email chain where the decisions actually get made.
Most consultants build dashboards on top of the mess. Most AI consultants demo prototypes that never touch the real workflow. FinData builds the infrastructure that makes both actually work, grounded in how service businesses run, not a generic template.
- “You shouldn’t have to wait three weeks to know what last month looked like.”
- “Your forecast shouldn’t live in one analyst’s laptop.”
- “Your dispatch data shouldn’t require a human to reconcile it every Friday.”
Infrastructure for decisions.
Business Intelligence & Reporting
Power BI implementation, semantic models, DAX, governance. Operational and marketing performance reporting built for decisions, not for theater. Dashboards operators actually use.
FP&A & Financial Systems
Budgeting, forecasting, and financial modeling that scales past where spreadsheets break. Finance and operations finally see the same numbers.
Financial & Operational Modeling
Enterprise-grade financial models, operational workbooks, and decision tools. Delivered in days, not weeks. Structured so the people who didn’t build them can still run them in production.
AI Implementation
Practical AI deployed where it earns its keep. Agents, copilots, model routing, forecasting augmentation, knowledge assistants, and governance. Platform-agnostic, scoped to your business problem, built to last past the implementation.
Data Infrastructure & Automation
SQL, Snowflake, Power Platform, Power Query. Common datasets that consolidate Workday, multiple QuickBooks companies, Sage, CRM, marketing platforms, and field tools so reporting and AI analysis have one trusted base.
Fractional Systems Leadership
Senior finance, BI, marketing analytics, and AI leadership on a fractional or project basis. Director-level systems thinking without the headcount commitment.
A spreadsheet is software. We build it that way.
Enterprise-grade financial models, operational workbooks, and decision tools, delivered in days instead of weeks. Built with the structure of real software: documented, auditable, handoff-ready. Operated by the people who didn’t build them.
Most business-critical spreadsheets are held together by one person’s memory. When that person leaves, the model leaves. When the business grows, the model breaks. When someone new needs to use it, training takes weeks.
We build the opposite. Real structure. Clean interfaces anyone can run. Logic that survives handoff. Speed without shortcuts. Most of what we build started as a conversation about a spreadsheet someone was afraid to change, and ended as something a new hire could use on day one.
- 01Financial models. FP&A, forecasting, scenario planning, cash flow.
- 02Operational workbooks. Job costing, route profitability, margin analysis, capacity planning.
- 03Decision tools. Pricing calculators, bid estimators, scenario comparators.
- 04Real-time workflows. Live calculations, reconciliation engines, operator-facing interfaces.
- 05Common reporting datasets. Workday, multiple QuickBooks companies, Sage, and other finance systems consolidated into Airtable, Snowflake, or Power Platform for BI and AI model analysis.
- Scale without breaking when the data does.
- Run without the builder in the room.
- Hand off cleanly to non-technical operators.
- Audit cleanly when something goes wrong.
Enterprise-grade operational tool, built in days instead of weeks. Real-time workflows. Complex backend logic, simple operator interface. Non-technical users running it live in production.
The class of work most consultants scope as a multi-month engagement. We scope it in days because we’ve already built the patterns that make it fast, and because async delivery means no calendar tetris.
Business problem first. AI second.
Most AI consulting is one of two things: enterprise implementations that take 18 months and seven figures, or productivity hacks that amount to “here are some ChatGPT prompts.”
Service-based businesses and operational SMBs need something else: AI that plugs into the systems you already run, delivers measurable time and cost savings, and doesn’t require an in-house AI team to keep it alive.
Most consultants sell one platform. We use whichever one fits.
Each major AI platform has a distinct sweet spot. Claude handles long, careful work. ChatGPT moves quickly across tools and prototypes. Gemini lives inside Google Workspace. Copilot lives inside Microsoft 365. Grok sees X and the live web. Perplexity grounds research in sources. Open-weight models give you control.
The useful question is not which AI is best. It is which model, connector, agent, and review path fits the workflow. We build the workflow first, then pick the tools that fit.
Tools are agnostic. They should be used that way.
- 01ClaudeAnthropicLong-horizon analysis, document-heavy work, code review, finance/legal reasoning, and high-resolution visual review. Strong when quality control matters more than speed.
- 02ChatGPTOpenAIBroadest ecosystem for professional work: research, coding, spreadsheets, documents, plugins, and computer-use agents. Strong default when prototypes need to become workflows.
- 03GeminiGoogleBest when work lives in Google Workspace. Gemini 3.5 and Spark point toward fast agents across Gmail, Docs, Sheets, Slides, Search, and Android.
- 04CopilotMicrosoftBest inside Microsoft 365. Copilot Chat, Excel editing, Teams, Agent 365, and model-diverse Frontier features make it the enterprise-governed path.
- 05GrokxAIReal-time X/web context, large-context API work, and agent tool calling. Useful when the answer depends on live market, public conversation, or current-event signals.
- 06PerplexityPerplexity AICited research plus Comet and Computer workflows for browser, finance, and data-science work. Useful when answers need sources and repeatable web-grounded tasks.
- 07Open-weightsLlama, Mistral, othersLlama, Mistral, and similar models for privacy-sensitive, high-volume, edge, or self-hosted workloads where control matters more than a polished chat UI.
The platforms are moving from answers to action. That changes the implementation work.
The newest releases are less about better chat and more about agents that can use tools, operate inside workspaces, search live sources, and touch real files. That is useful only when the workflow has boundaries.
Agents moved into the workspace
Copilot, Gemini, ChatGPT, and Perplexity now reach across files, browsers, meetings, email, spreadsheets, and code. The implementation question is no longer "can it answer?" It is permissions, logging, review, and handoff.
Model routing beats model loyalty
The better architecture sends each task to the right model for the job: reasoning, search, document work, spreadsheet analysis, visual review, or low-cost repetition. One vendor rarely owns every workflow.
Computer use is becoming practical
Frontier models are getting better at operating software, browsers, and file systems. That creates real automation opportunities, but only with scoped access, stop conditions, exception queues, and human approval for high-stakes actions.
Open weights are real operating options
Llama, Mistral, and other open-weight releases make private, edge, and cost-sensitive deployments more realistic when data sensitivity or repeat volume makes SaaS chat the wrong fit.
The work AI does best isn’t glamorous. It’s the work that compounds.
The right implementation saves an hour a day on a task you do every day. Multiply that across a team, a year, and a workflow nobody enjoys, and the math gets serious quickly.
Pulling structured data out of invoices, work orders, and contracts. Routing to the right system automatically.
Matching incoming tickets to the right technician by skill, location, availability, and history.
Plain-language Q&A, variance explanation, and workbook updates over your actual data. No dashboard navigation, no SQL, no analyst in the loop for first-pass answers.
First-draft replies, follow-ups, and quotes generated from your tone and your context. Human-edited, sent in minutes.
Searchable, conversational interfaces over your SOPs, training docs, and institutional knowledge.
Models that learn from your sales history, seasonality, and operational patterns instead of generic curves.
Turning a customer name into address, industry, contact info, and financial data. Automatically, on demand.
Summarizing 50-page documents into the three things that matter. First-pass legal and commercial review.
Automating repetitive work across email, files, calendars, browsers, and spreadsheets with human approvals, logs, and fallback rules.
Choosing the right model for each task, setting data boundaries, testing output quality, logging usage, and controlling cost before AI usage spreads.
Who we work with
- Trades and contractors scaling beyond the owner’s capacity.
- Field service and equipment operators in multi-market expansion.
- Independent real estate agents who need a stronger technical bench behind their client service.
- Distribution, logistics, and fleet operations.
- B2B suppliers and equipment dealers.
- Family-owned operators at $5M–$100M in revenue.
- PE-backed operational businesses needing post-acquisition integration.
How we work
Async-first engagements. No standing Zoom calls. Scoped work, visible progress, finished deliverables. Most engagements run 4–12 weeks. Retainers available.
Intake questionnaire
We define the problem in writing. No discovery calls.
Written diagnostic
Analysis and recommendations delivered as a document.
Scoped proposal
Fixed deliverables, defined timeline, transparent pricing.
Execution
Async check-ins and Loom walkthroughs for every deliverable.
The force multiplier, in four parts.
The operator bridge
Most BI consultants have never set foot in a yard, a warehouse, or a service truck. Most operations consultants don’t know what DAX is. FinData operates at both ends.
Senior expertise, fractional footprint
15+ years of director-level BI, finance, and marketing analytics leadership across the tax, accounting, and software industries. Certified across the major analytics, attribution, and AI platforms. Built from scratch, not pulled from templates.
Systems, not theater
Finance, BI, data, and AI designed to work together. Not isolated tools glued into a slide deck. Not dashboards that look impressive and get ignored.
Async by design
Scoped work, fixed deliverables, no retainer padding. No standing Zoom calls. No status meetings that should have been emails.
Practical guidance for systems that survive real operations.
The High-Touch Agent Does Not Need Another App. They Need a Better Operating System.
A practical guide to turning the tools an agent already uses into a more responsive client-service, market-intelligence, and business-visibility system.
A Spreadsheet Is Software. Build It That Way.
A practical field guide for turning fragile workbooks into durable decision tools that can survive growth, handoff, and real operator use.
Most Service Businesses Do Not Have a Data Problem. They Have a Visibility Problem.
A practical approach to building reporting that operators actually use, starting with decisions and workflow instead of dashboard theater.
Ready to fix the system?
Tell us what’s broken. We’ll tell you what it takes to fix it.
See how these capabilities become a field-ready support system for Real Estate Agents.
Finance, data, and AI systems for businesses scaling beyond what spreadsheets can hold.
AI is an unbelievable tool. It also needs the right context, the right scope, and the right hands.
We bring all three. The diagnosis of what’s actually worth automating. The discipline to keep the implementation small. The operator’s eye for whether the thing we built is going to survive contact with a real workday.
Augusta-based consulting for service-based businesses and operational SMBs that need senior finance, BI, and AI expertise without the full-time hire.
Most service businesses don’t have a data problem. They have a visibility problem.
The data exists. It’s trapped in seven different places: the field app, the billing system, the spreadsheet one person knows how to update, the email chain where the decisions actually get made.
Most consultants build dashboards on top of the mess. Most AI consultants demo prototypes that never touch the real workflow. FinData builds the infrastructure that makes both actually work, grounded in how service businesses run, not a generic template.
- “You shouldn’t have to wait three weeks to know what last month looked like.”
- “Your forecast shouldn’t live in one analyst’s laptop.”
- “Your dispatch data shouldn’t require a human to reconcile it every Friday.”
Infrastructure for decisions.
Business Intelligence & Reporting
Power BI implementation, semantic models, DAX, governance. Operational and marketing performance reporting built for decisions, not for theater. Dashboards operators actually use.
FP&A & Financial Systems
Budgeting, forecasting, and financial modeling that scales past where spreadsheets break. Finance and operations finally see the same numbers.
Financial & Operational Modeling
Enterprise-grade financial models, operational workbooks, and decision tools. Delivered in days, not weeks. Structured so the people who didn’t build them can still run them in production.
AI Implementation
Practical AI deployed where it earns its keep. Agents, copilots, model routing, forecasting augmentation, knowledge assistants, and governance. Platform-agnostic, scoped to your business problem, built to last past the implementation.
Data Infrastructure & Automation
SQL, Snowflake, Power Platform, Power Query. Common datasets that consolidate Workday, multiple QuickBooks companies, Sage, CRM, marketing platforms, and field tools so reporting and AI analysis have one trusted base.
Fractional Systems Leadership
Senior finance, BI, marketing analytics, and AI leadership on a fractional or project basis. Director-level systems thinking without the headcount commitment.
A spreadsheet is software. We build it that way.
Enterprise-grade financial models, operational workbooks, and decision tools, delivered in days instead of weeks. Built with the structure of real software: documented, auditable, handoff-ready. Operated by the people who didn’t build them.
Most business-critical spreadsheets are held together by one person’s memory. When that person leaves, the model leaves. When the business grows, the model breaks. When someone new needs to use it, training takes weeks.
We build the opposite. Real structure. Clean interfaces anyone can run. Logic that survives handoff. Speed without shortcuts. Most of what we build started as a conversation about a spreadsheet someone was afraid to change, and ended as something a new hire could use on day one.
- 01Financial models. FP&A, forecasting, scenario planning, cash flow.
- 02Operational workbooks. Job costing, route profitability, margin analysis, capacity planning.
- 03Decision tools. Pricing calculators, bid estimators, scenario comparators.
- 04Real-time workflows. Live calculations, reconciliation engines, operator-facing interfaces.
- 05Common reporting datasets. Workday, multiple QuickBooks companies, Sage, and other finance systems consolidated into Airtable, Snowflake, or Power Platform for BI and AI model analysis.
- Scale without breaking when the data does.
- Run without the builder in the room.
- Hand off cleanly to non-technical operators.
- Audit cleanly when something goes wrong.
Enterprise-grade operational tool, built in days instead of weeks. Real-time workflows. Complex backend logic, simple operator interface. Non-technical users running it live in production.
The class of work most consultants scope as a multi-month engagement. We scope it in days because we’ve already built the patterns that make it fast, and because async delivery means no calendar tetris.
Business problem first. AI second.
Most AI consulting is one of two things: enterprise implementations that take 18 months and seven figures, or productivity hacks that amount to “here are some ChatGPT prompts.”
Service-based businesses and operational SMBs need something else: AI that plugs into the systems you already run, delivers measurable time and cost savings, and doesn’t require an in-house AI team to keep it alive.
Most consultants sell one platform. We use whichever one fits.
Each major AI platform has a distinct sweet spot. Claude handles long, careful work. ChatGPT moves quickly across tools and prototypes. Gemini lives inside Google Workspace. Copilot lives inside Microsoft 365. Grok sees X and the live web. Perplexity grounds research in sources. Open-weight models give you control.
The useful question is not which AI is best. It is which model, connector, agent, and review path fits the workflow. We build the workflow first, then pick the tools that fit.
Tools are agnostic. They should be used that way.
- 01ClaudeAnthropicLong-horizon analysis, document-heavy work, code review, finance/legal reasoning, and high-resolution visual review. Strong when quality control matters more than speed.
- 02ChatGPTOpenAIBroadest ecosystem for professional work: research, coding, spreadsheets, documents, plugins, and computer-use agents. Strong default when prototypes need to become workflows.
- 03GeminiGoogleBest when work lives in Google Workspace. Gemini 3.5 and Spark point toward fast agents across Gmail, Docs, Sheets, Slides, Search, and Android.
- 04CopilotMicrosoftBest inside Microsoft 365. Copilot Chat, Excel editing, Teams, Agent 365, and model-diverse Frontier features make it the enterprise-governed path.
- 05GrokxAIReal-time X/web context, large-context API work, and agent tool calling. Useful when the answer depends on live market, public conversation, or current-event signals.
- 06PerplexityPerplexity AICited research plus Comet and Computer workflows for browser, finance, and data-science work. Useful when answers need sources and repeatable web-grounded tasks.
- 07Open-weightsLlama, Mistral, othersLlama, Mistral, and similar models for privacy-sensitive, high-volume, edge, or self-hosted workloads where control matters more than a polished chat UI.
The platforms are moving from answers to action. That changes the implementation work.
The newest releases are less about better chat and more about agents that can use tools, operate inside workspaces, search live sources, and touch real files. That is useful only when the workflow has boundaries.
Agents moved into the workspace
Copilot, Gemini, ChatGPT, and Perplexity now reach across files, browsers, meetings, email, spreadsheets, and code. The implementation question is no longer "can it answer?" It is permissions, logging, review, and handoff.
Model routing beats model loyalty
The better architecture sends each task to the right model for the job: reasoning, search, document work, spreadsheet analysis, visual review, or low-cost repetition. One vendor rarely owns every workflow.
Computer use is becoming practical
Frontier models are getting better at operating software, browsers, and file systems. That creates real automation opportunities, but only with scoped access, stop conditions, exception queues, and human approval for high-stakes actions.
Open weights are real operating options
Llama, Mistral, and other open-weight releases make private, edge, and cost-sensitive deployments more realistic when data sensitivity or repeat volume makes SaaS chat the wrong fit.
The work AI does best isn’t glamorous. It’s the work that compounds.
The right implementation saves an hour a day on a task you do every day. Multiply that across a team, a year, and a workflow nobody enjoys, and the math gets serious quickly.
Pulling structured data out of invoices, work orders, and contracts. Routing to the right system automatically.
Matching incoming tickets to the right technician by skill, location, availability, and history.
Plain-language Q&A, variance explanation, and workbook updates over your actual data. No dashboard navigation, no SQL, no analyst in the loop for first-pass answers.
First-draft replies, follow-ups, and quotes generated from your tone and your context. Human-edited, sent in minutes.
Searchable, conversational interfaces over your SOPs, training docs, and institutional knowledge.
Models that learn from your sales history, seasonality, and operational patterns instead of generic curves.
Turning a customer name into address, industry, contact info, and financial data. Automatically, on demand.
Summarizing 50-page documents into the three things that matter. First-pass legal and commercial review.
Automating repetitive work across email, files, calendars, browsers, and spreadsheets with human approvals, logs, and fallback rules.
Choosing the right model for each task, setting data boundaries, testing output quality, logging usage, and controlling cost before AI usage spreads.
Who we work with
- Trades and contractors scaling beyond the owner’s capacity.
- Field service and equipment operators in multi-market expansion.
- Independent real estate agents who need a stronger technical bench behind their client service.
- Distribution, logistics, and fleet operations.
- B2B suppliers and equipment dealers.
- Family-owned operators at $5M–$100M in revenue.
- PE-backed operational businesses needing post-acquisition integration.
How we work
Async-first engagements. No standing Zoom calls. Scoped work, visible progress, finished deliverables. Most engagements run 4–12 weeks. Retainers available.
Intake questionnaire
We define the problem in writing. No discovery calls.
Written diagnostic
Analysis and recommendations delivered as a document.
Scoped proposal
Fixed deliverables, defined timeline, transparent pricing.
Execution
Async check-ins and Loom walkthroughs for every deliverable.
The force multiplier, in four parts.
The operator bridge
Most BI consultants have never set foot in a yard, a warehouse, or a service truck. Most operations consultants don’t know what DAX is. FinData operates at both ends.
Senior expertise, fractional footprint
15+ years of director-level BI, finance, and marketing analytics leadership across the tax, accounting, and software industries. Certified across the major analytics, attribution, and AI platforms. Built from scratch, not pulled from templates.
Systems, not theater
Finance, BI, data, and AI designed to work together. Not isolated tools glued into a slide deck. Not dashboards that look impressive and get ignored.
Async by design
Scoped work, fixed deliverables, no retainer padding. No standing Zoom calls. No status meetings that should have been emails.
Practical guidance for systems that survive real operations.
The High-Touch Agent Does Not Need Another App. They Need a Better Operating System.
A practical guide to turning the tools an agent already uses into a more responsive client-service, market-intelligence, and business-visibility system.
A Spreadsheet Is Software. Build It That Way.
A practical field guide for turning fragile workbooks into durable decision tools that can survive growth, handoff, and real operator use.
Most Service Businesses Do Not Have a Data Problem. They Have a Visibility Problem.
A practical approach to building reporting that operators actually use, starting with decisions and workflow instead of dashboard theater.
Ready to fix the system?
Tell us what’s broken. We’ll tell you what it takes to fix it.