Boutique FDE-Guided AI Deployment Firm

Boutique AI deployment firm for the modern enterprise.

We Transform Human-Driven Workflows Into Recursive Self-Improving WorkLoops™ That Run Autonomously Inside Your Company's Claude, OpenAI, Or Gemini Account

FirmBoutique AI deploymentPrivate. Engineering-led. Miami.
ExclusivityBy application onlyLimited cohort. 4 engagements per quarter.
TeamEx-Silicon Valley engineersOne Forward Deployed Engineer per account.
DeploymentLive in 14 daysKickoff to first WorkLoop in production.
HalcyonAtlasForgeNorthwindSigma/coVance
HalcyonAtlasForgeNorthwindSigma/coVance
Why 95% AI deployments fail

The AI models work.
Deployment is the problem.

MIT found 95% of enterprise AI pilots deliver zero measurable impact — and the cause isn't model quality. It comes down to four structural failures in how AI gets deployed.

Failure #1

Manual workflow capture

Traditional deployment works with one domain expert at a time — there's no scalable way in, so rollout is slow and never reaches the whole org.

Scalable Org Deployment Wedge

Scalable Video-to-WorkLoop capture

Video-to-WorkLoop is the wedge: film a workflow once, then an engineer calibrates it into automation in your connected AI account — fast, across the whole org.

Failure #2

Breaks in production

Your experts know the work, not how to build automations that survive production — or even which ones are worth building. So they break.

WorkLoop Auto-Generation

Production-level WorkLoops

WorkAGI auto-generates the right WorkLoops for you, production-grade — decision logic and edge cases built in. No AI skill needed from your team.

Failure #3

Complicated new tech stack

A whole new platform bolted onto your stack — new logins and new integrations to build and maintain on top of everything you already run.

Zero New Integrations

Same existing tech stack

Zero changes to your stack. Our MCP server runs inside your connected AI accounts and piggybacks the integrations you already use.

Failure #4

Decaying static automation

Months to build, then it decays — performance drops, hallucinations creep in, and you pay a retainer for life just to keep it usable.

Self-Improving WorkLoops

Self-improves over time

WorkLoops self-improve from your feedback automatically — staying current and sharpening over time, with little to no manual effort.

Most AI never reaches production.

WorkAGI does.

Schedule a demo
Customized AI Deployment

Most AI Deployment Fails.
WorkAGI Software & FDE Model Wins.

Software alone produces demos. Consulting alone produces decks. WorkAGI pairs both — productized software deployed by a senior engineer — so AI actually reaches production.

Step 1

Capture Workflows

Your team films a workflow once — Loom, screen recording, or SOP doc. WorkAGI ingests it.

LoomVideoDocsAudio
Step 2

Compile .WorkAGI File

WorkAGI compiles the capture into a structured .workagi file — the executable definition of the work.

TranscriptScene CaptureScreen Mapping
Step 3

Run WorkLoops

Your AI executes the WorkLoop on demand or on schedule. Every run is traced. Every result feeds the improvement loop.

ClaudeGPTGemini
WorkAGI automation layer

The modern AI-first organization stack.

Your software. Your AI. The work-automation layer that ties them together.

Layer 1
WorkAGI automation platform

WorkAGI

Captures workflows and runs them across your AI tools and your existing software.

CaptureCompileRunTraceSelf-ImproveSchedule
Runs inside your AI
Layer 2
Your AI interface

Your existing AI Provider

Where your team works. WorkLoops appear as native tools inside whichever AI you already use.

ClaudeGPTGemini+MCP-compatible
Automates your software
Layer 3
Your business systems

Your existing software

CRM, email, database, and 200+ business apps. Connected through standard OAuth.

HubSpotSalesforceGmailSlackClickupFigmaAsanaShopifyNotionMailchimpZoomQuickbooksTrelloZendeskDropbox+200 more
Workflows vs WorkLoops™

Workflows are dead. WorkLoops™ are here.

A workflow is what your team did yesterday. A WorkLoop™ is what runs across your stack today. Captured once. Executing forever. Improving with every run.

Pre-AI Paradigm

Traditional Human-Driven Workflow

A static sequence of steps. Executed by one employee. Knowledge stored in their head.

Employee
01 · Task
02 · Task
03 · Task
04 · Forgotten
05 · Dead-End
ExecutionLinear
MemoryTacit
ScalingHeadcount
ImprovementManual
WorkAGI Paradigm

Recursive Self-Improving WorkLoop™

A system that captures the workflow, runs it, and gets better with every execution. Knowledge stays in the platform.

WorkLoop
CaptureExecuteFeedbackSelf Improve
ExecutionCyclical
MemoryIn Platform
ScalingIndependent
ImprovementContinuous
Use Cases

WorkAGI Automation Use Cases

Explore the wide range of processes we can automate for your business

Data Processing & Migration

Automatically collect, process, and transfer data between systems

Common Examples
  • CRM data sync
  • Report generation
  • Database migrations

Customer Communications

Streamline customer interactions and follow-ups

Common Examples
  • Email campaigns
  • Support ticket routing
  • Follow-up sequences

Financial Operations

Automate accounting and financial processes

Common Examples
  • Invoice processing
  • Expense reporting
  • Payment reconciliation

HR & Onboarding

Simplify human resources and employee management

Common Examples
  • Employee onboarding
  • Time tracking
  • Performance reviews

Sales & Marketing

Optimize lead generation and nurturing processes

Common Examples
  • Lead scoring
  • Campaign management
  • Pipeline updates

Inventory Management

Automate stock tracking and procurement processes

Common Examples
  • Stock alerts
  • Reorder automation
  • Supplier communications
Time Savings

Reduce manual work by 50-80%

Automate repetitive tasks and free up your team for strategic work

Cost Reduction

Lower operational expenses

Eliminate inefficiencies and reduce the need for additional staff

Accuracy Improvement

99.9% error reduction

Eliminate human errors and ensure consistent, reliable processes

Scalability

Grow without friction

Scale your operations without proportionally increasing overhead

AI-Native File Architecture

Introducing.workagi.

WorkAGI invented a proprietary file format for AI work automation with context-rich unified audio and visual workflow capture. Loom is how humans record work. .workagi is how AI learns it.

For Humans
Loom
How humans record work.
For AI
.workagi
How AI learns it
Before
workflow.mp4
File size247 MB
AI ingestion latency142 sec
Storage / user / yr$4.80
Security postureIncidental PII
AI-nativeNo
After
workflow.workagi
File size412 KB
AI ingestion latency87 ms
Storage / user / yr$0.004
Security postureCryptographically signed
AI-nativeYes
1000Smaller than video100–500 KB instead of 200–500 MB. Same workflow intelligence, one thousandth the storage.
10,000Cheaper to queryPure structured text. No multimodal model inference required per query.
<100 msAI ingestionFiles arrive in the agent context window immediately. Zero preprocessing.
100%Portable & ownedDownload anytime. Upload to Claude, ChatGPT, Gemini, or any AI tool you operate.
Privacy-first Workflow capture

Employee-centric privacy is the architecture.

Employees opt-in and film what they choose. Recordings auto-delete after compilation. Only the structured WorkLoop remains. Capture without surveillance.

Guarantee 1

You own your data.

Every .workagi file is yours. Downloadable anytime. Portable to any AI tool. No vendor lock-in. No data hostage situations at renewal.

Guarantee 2

Employee-initiated, not surveillance.

Recordings only happen when an employee starts one, for a specific workflow they want to automate. No continuous monitoring. No background capture.

Guarantee 3

Raw recordings auto-delete.

Source videos are scaffolding, not assets. They auto-delete within 24 hours of compilation. Only the structured .workagi file persists.

Guarantee 4

Audit-ready by default.

Every .workagi file is cryptographically signed at generation. Every execution is traced step-by-step. Compliance review takes minutes, not weeks.

FDE-Guided AI Deployment

Customized installation by your
Forward-Deployed Engineer.

No self-serve onboarding. No shared support queue. One senior engineer, accountable to your account, from kickoff through your first production quarter.

Phase 1

Invite

We provision your team. Everyone gets a magic-link invite.

Phase 2

Capture

Your team records workflows via Loom or screen recording.

Phase 3

Compile

We compile the captures into reliable WorkLoops.

Phase 4

Calibrate

Your FDE leads a four-week calibration cycle.

Phase 5

Run

WorkLoops run on demand inside chat, or on a schedule.

Why WorkAGI

WorkAGI > Everything Else.

Traditional AI deployments take more than a year and ship a static deliverable. WorkAGI engagements ship a self-improving system in two weeks.

Conventional Approach

Traditional AI deployment

Services firm or in-house build

60+weeks
Average time to production
Week 0

Discovery & Scoping

Stakeholder interviews. Requirements gathering.

Week 4

Vendor RFP

Proposals collected. Demos. Vendor selection.

Week 8

Contract & SOW

Legal review. Procurement. Statement of work signed.

Week 14

Architecture design

Technical specifications. Integration planning.

Week 20

Data integration

Pipelines wired. Security review.

Week 28

Custom development

Build cycle. External agency or internal team.

Week 40

Internal QA

Testing. Bug fixes. Compliance review.

Week 48

Pilot program

Limited rollout. Feedback collection.

Week 54

Team training

Workshops. Documentation. Change management.

Week 60

Production rollout

Go-live. Vendor exits. Maintenance contract begins.

Outcome

$500K – $2M

Total first-year cost
  • Static deliverable
  • Decays without maintenance
  • Institutional knowledge leaves with vendor
  • Renegotiation required for every change
WorkAGI Engagement

WorkAGI + Forward Deployed Engineer

A senior engineer assigned to your account

14days
First WorkLoop in production
Day 1

Apply

Ninety-second intake. Engagement criteria validated.

Day 2

Qualification call

Thirty-minute review with the founding team.

Day 3

FDE assigned

Senior engineer embeds with your team.

Day 5

Workflow capture

Employees record workflows. Platform extracts definitions.

Day 10

Compile & calibrate

WorkLoops generated. FDE-led calibration cycle.

Day 14

Live in production

WorkLoops execute on demand or on schedule.

Outcome

Customized Pricing

Tailored to engagement scope
  • Downloadable Skills
  • Self-improving system
  • Improves with every execution
  • Institutional memory retained in platform
Time to production30× faster
First-year cost95% lower
Quality trajectoryImproving vs decaying
Knowledge retentionRetained vs lost
Multi-Model Compatibility

Connect your Claude, ChatGPT, or
Gemini Team account with 1-click.

One OAuth connection. Every WorkLoop becomes a tool inside your AI. Employees invoke them in chat, on schedule, or by command. No migration, no retraining.

Claude

WorkLoops appear as native tools inside Claude. Built on Anthropic's Model Context Protocol.

AuthOAuth · BYOK

ChatGPT

WorkLoops execute as ChatGPT actions. Works across Plus, Team, and Enterprise.

AuthOAuth · BYOK

Gemini

WorkLoops run as Gemini extensions. Workspace and Enterprise both supported.

AuthOAuth · BYOK
Case studies

Production WorkLoops, deployed
at operating companies.

Three engagements. Three companies. One model. Every WorkLoop in this section is running in production today.

Sigma Partners

B2B SaaS24 EmployeesSeries A

We replaced a contracted role within two weeks of kickoff. By the end of the quarter, our smaller team was outperforming the previous structure on every pipeline metric we track.

$340KAnnualized labor savings
11 daysFirst WorkLoop in production

Halcyon Growth

Marketing Operations41 Employees

Previous AI engagements produced deliverables that aged out within weeks. WorkAGI shipped a working system in our environment and continued improving it after handover.

62Live WorkLoops
3.4×Output per FTE
Questions, answered

Frequently Asked Questions

Limited Availability

See if you qualify.
By application only.

Ninety-second application. Thirty-minute qualification call.

See If You Qualify
Current cohortQ3 2026
Application90 seconds
Qualification call30 minutes
InvestmentCustomized Pricing
SOC 2 Type II · in progressSSO / SAMLBYOKEU residency · on requestMSA · standard terms