Email & Follow-ups
Before:Manual follow-ups that get forgotten
After:Automatic sequences triggered by customer actions
Visible follow-up status
AI and automation
Automate the repetitive work
LLM agents, OCR pipelines, and trained ML models that replace the copy-paste work. Built on Gemini, GPT-4 and your own data.
Kills Busywork
No more copy-paste between systems
Grounded in your docs
Retrieval over your own data
Cited answers
Answers cite your knowledge base
Always on
Runs outside office hours
TL;DR
We build Gemini 3.1 Live, Gemini Flash and GPT-4 agents grounded in your documents through retrieval, plus OCR document extraction and predictive models, and connect them to your stack behind typed APIs. Most automations go live in 2-4 weeks; custom ML projects take 6-8.
Common tasks
Where the time goes
These are the tasks we automate most often
Appointment Booking
Before:Phone tag and missed calls
After:Self-service booking with automatic reminders
Reduces scheduling friction
Lead Response
Before:Leads wait hours or days for response
After:Faster response, 24/7 availability
Faster response
Data Entry
Before:Copy-paste between systems all day
After:Systems sync automatically in real-time
Less repeated data entry
Models
Models and tooling
LLMs, embeddings and ML models connected to your stack through REST and webhooks
Conversational Agents
Voice and text agents grounded in approved information, connected to defined tools and evaluated against real visitor or team tasks
- Retrieval from an approved knowledge base
- Bounded tools and permission checks
- Human review before consequential actions
- Voice and text with clear fallback paths
Document Extraction
OCR plus LLM parsing pulls line-items, totals, and entities from invoices, contracts, and forms into your systems
- Tesseract + vision model OCR
- Structured JSON output to your API
- Confidence scoring and human review queue
- Handles scans, PDFs, and photos
Predictive Models
Churn, demand, and lead-scoring models trained on your historical data and deployed behind an API
- Gradient-boosted churn models
- Time-series demand forecasting
- Lead scoring with feature importance
- Retraining pipelines on fresh data
Integrations
Connects to tools you already use
CRM, billing, messaging and spreadsheets, connected so data moves between them
- CRM
- Salesforce / HubSpot / Zoho / Pipedrive
- Finance
- QuickBooks / Xero
- Payments
- Stripe / Square
- Communication
- Slack / Teams
- Productivity
- Google Workspace / Microsoft 365
- E-commerce
- Shopify / WooCommerce
- Marketing
- Mailchimp
- Custom
- Custom APIs
Don't see your tool? We can probably connect it.
Process
How we implement automation
- 1
Audit
We map your current workflows and find the repetitive steps
- 2
Build
We automate one process at a time, testing each thoroughly
- 3
Train
Your team learns the new system with hands-on training
Most automations are live within 2-4 weeks. Complex AI projects take 6-8 weeks.
Results show up once the systems are live and running
Agent workflows
From a prompt to a reviewable result
The useful part is the completed job: what the agent can access, what it can change and how a person checks the result.
- 01
Define the job
Choose one workflow, its inputs and the result your team needs. Set access limits and identify actions that require a person to approve them.
- 02
Connect the tools
Connect the relevant APIs, documents and business systems. Give the workflow clear ownership, visible progress and a way to recover from a failed step.
- 03
Verify the result
Test representative tasks and failure paths, review the output and document the handoff. Expand the workflow only after the first useful outcome is dependable.
Our internal JarvisMCP work applies this approach to capability discovery, task coordination and guarded tool execution. It is our own internal work, not a client result.
FAQ
Frequently asked questions
Common questions about scope, data and timelines for AI automation.
What kind of AI solutions do you build for businesses?
Customer service chatbots, document processing, forecasting dashboards and custom models for a specific problem. We start with the problem and only use AI where it pays for itself.
Can AI really help small businesses in Fort Lauderdale?
Yes. AI tools are now accessible to businesses of all sizes. A local restaurant can use AI for inventory prediction. A law firm can use it for document review. A contractor can use AI chatbots for after-hours lead capture. We right-size solutions to your budget and needs.
How do you integrate AI with existing business systems?
We connect AI tools to your CRM, ERP, phone system and databases through APIs. For example, a chatbot can check inventory, book an appointment in your calendar and create a lead in your CRM.
What's the difference between AI automation and regular automation?
Regular automation follows fixed rules: if this, then that. AI automation can handle variation, read natural language and make predictions from patterns, so it covers tasks that fixed rules cannot.
How long does it take to implement an AI solution?
A chatbot connected to your data takes weeks. A custom model trained on your data takes months. We usually start with a small pilot so you can judge it before spending more.
Work
Related case studies
Our own engineering systems: governed agent tooling, search intelligence and an embedded-agent prototype.
- Developer ToolsJarvisMCPJarvisMCP gives AI agents one governed door into our company systems: CRM, search intelligence, infrastructure, memory and coordination. Agents find the capability they need, act through it, and leave a record. They never hold the keys.View case study
- Sales & MarketingOverwatchOverwatch shows how a site is found in classic search, in AI answers and on the local map, then proposes the fixes. Nothing it proposes reaches a live site until a person approves it.View case study
- AI & Machine LearningJarvisNanoAn open-source embedded AI project with C/C++ firmware on Seeed XIAO ESP32-S3 Sense and Waveshare AMOLED boards, dynamically loaded Lua skills running on-chip, and hardware-first prototyping to explore assistants that run on a device. A Kotlin Android app is the optional companion.View case study
Automate the work your team repeats every week
An AI workflow connected to your CRM, inbox or documents, tested on your real cases before it goes live
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