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Fitwork AI
Services

AI systems, built around how the work actually happens.

Six ways Fitwork applies AI to real business workflows — each one designed around the problem, not the technology.

01

AI Voice Agents

The problem: Calls go unanswered after hours, and qualifying every lead by phone doesn't scale with a small team.

What we build: An AI phone agent that answers, understands intent, and takes the next action — booking, qualifying, or routing to a human when it should.

  • Inbound support
  • Lead qualification
  • Appointment booking
  • Outbound calling
  • Follow-ups
ai-voice-agents.flow()
Call inInbound or outbound call begins.
AI AgentUnderstands intent and context.
ActionQualifies, books, or escalates.
CRM / CalendarOutcome logged automatically.
Example use cases
A missed call after hours becomes a qualified lead by morning.
A service business books appointments without anyone picking up the phone.
Implementation approach
  1. 01Discover current call flows and scripts
  2. 02Design the conversation logic and escalation rules
  3. 03Build and connect the telephony and AI agent
  4. 04Integrate with CRM and calendar systems
  5. 05Monitor call quality and refine
02

AI Chat Agents

The problem: Customers expect an instant answer on WhatsApp and the website — most teams can't staff that around the clock.

What we build: Conversational agents that resolve common questions, qualify leads, and know exactly when to bring in a human.

  • WhatsApp
  • Website chat
  • Customer support
  • Lead qualification
  • Internal knowledge
ai-chat-agents.flow()
MessageCustomer reaches out.
AI AgentReads intent and context.
KnowledgeGrounded in real business info.
ResolutionAnswered, or handed to a human.
Example use cases
A WhatsApp agent answers product questions instantly, day or night.
A website agent qualifies a visitor before a sales call is even booked.
Implementation approach
  1. 01Map the most common conversations and questions
  2. 02Design agent behavior, tone, and guardrails
  3. 03Build and train the agent on real knowledge
  4. 04Integrate with WhatsApp and the website
  5. 05Refine from real conversation data
03

AI Workflow Automation

The problem: The same data gets typed into three systems by three different people, every single day.

What we build: Automation that connects the steps of a workflow — trigger, decision, and system update — so people only touch the exceptions.

  • Repetitive operations
  • CRM workflows
  • Document processing
  • Data extraction
  • Notifications
ai-workflow-automation.flow()
TriggerAn event starts the workflow.
ExtractRelevant data is identified.
Business rulesLogic decides what happens next.
System updateRecords update automatically.
Example use cases
A new order automatically updates inventory, billing, and shipping — no manual entry.
Expense documents are read, categorized, and logged without opening a spreadsheet.
Implementation approach
  1. 01Map the current manual workflow end to end
  2. 02Identify the steps that are safe to automate
  3. 03Build the automation and business rules
  4. 04Integrate with the tools already in use
  5. 05Monitor and expand coverage over time
04

Document Intelligence

The problem: Documents pile up — invoices, contracts, compliance paperwork — and someone has to read and re-key every one of them.

What we build: AI that reads documents, extracts the data that matters, and routes it into the right system automatically.

  • Invoice & receipt processing
  • Contract data extraction
  • Compliance document checks
  • Structured data export
document-intelligence.flow()
Document inA file or scan is received.
AI extractionKey fields are read out.
ValidationChecked against business rules.
Structured dataDelivered where it's needed.
Example use cases
A fleet operator's compliance paperwork is checked and filed automatically.
Invoices are read and posted to the accounting system without manual entry.
Implementation approach
  1. 01Collect a representative sample of real documents
  2. 02Design the extraction and validation logic
  3. 03Build the processing pipeline
  4. 04Integrate with the destination system
  5. 05Monitor accuracy and handle edge cases
05

AI Content Systems

The problem: Producing consistent, on-brand content at catalog scale is slow and expensive when it depends on manual shoots and editing.

What we build: A system that turns a product input into production-ready creative — built for ongoing scale, not one-off generation.

  • Product photography
  • Creative generation
  • Advertising content
  • Social content
  • Scalable production
ai-content-systems.flow()
InputA product photo or brief.
AI generationProduction visuals are produced.
ReviewChecked against brand standard.
Asset deliveredReady for use, at scale.
Example use cases
A product photo becomes a full set of catalog-ready images without a photo shoot.
Ad creative variations are generated at the pace a campaign actually needs.
Implementation approach
  1. 01Define the visual brand standard
  2. 02Design the generation pipeline
  3. 03Build and tune the generation models
  4. 04Integrate with the delivery channel
  5. 05Review and refine output quality
06

Custom AI Software

The problem: Sometimes the system a business needs doesn't exist yet — off-the-shelf tools don't fit how the business actually operates.

What we build: Full custom AI software — interface, AI logic, and infrastructure — built around a specific business, not a generic template.

  • Custom interfaces
  • AI-native application logic
  • APIs & infrastructure
  • Ongoing iteration
custom-ai-software.flow()
RequirementThe real operational need.
AI + app logicPurpose-built, not generic.
InfrastructureAPIs, data, deployment.
Live systemRunning the real workflow.
Example use cases
Fleet ERP: a full operating system built around how road transport actually runs.
A vertical AI product built from the ground up around one business's workflow.
Implementation approach
  1. 01Discover the real operational requirement
  2. 02Design the product and system architecture
  3. 03Build the application and AI logic
  4. 04Integrate and deploy the system
  5. 05Iterate as the product is used

Tell us what you want to automate.

We'll map the workflow, identify where AI can create leverage, and show you what we'd build.