unikode

The Platform for the AI Workforce

unikodeThe platform

Leadership

Introductions.

Farbod Gharaei, Founder and CEO of unikode
Founder & Chief Executive Officer

Farbod Gharaei

Farbod spent more than a decade leading digital transformation for large industrial and aerospace organizations, building the business systems their operations run on. He founded unikode so AI can carry real operational work under human direction.

Kelly O'Connell, Co-founder and Chief Operating Officer of unikode
Co-founder & Chief Operating Officer

Kelly O'Connell

Kelly's background spans operations strategy, corporate restructuring, and strategic projects, moving complex organizations from plan to execution. As COO he leads commercial scale, enterprise relationships, and client delivery.

unikode leadership02 / 09
unikodeThe platform

The shift

From AI tools to an AI workforce.

Enterprises added AI as point tools. The work still moves through people, inboxes, files, and systems.

Traditional work

People carry the process.

  • Knowledge lives in files, inboxes, meetings, and memory.
  • Capacity tracks headcount.
  • Coordination, handoffs, and manual review set the pace.
Current AI adoption

A point solution on top of the work.

  • An assistant, a chatbot, or a bolt-on to legacy systems.
  • It drafts and answers, but does not own the work path.
  • Routing, evidence, approvals, and follow-up happen elsewhere.
unikode's model

AI-native infrastructure for execution.

  • Business context becomes structured intelligence.
  • Managed AI workers run coordinated workflows.
  • People set direction, standards, and approvals.
  • Source, review, delivery, and records stay together.
  • unikode runs on unikodeThe platform built its own architecture, orchestration, agent workflows, and release machinery.
  • Builds itselfAutomated pipelines, validation gates, deployments, backlog, website, and product work run through the same model.
  • Operates itselfResearch, decks, content, delivery, and internal operations move under human direction.
  • Governance and approvalHumans set standards and approve consequential actions before delivery, publication, or external communication.
AI as infrastructure, not AI as tools03 / 09
unikode The platform

Difference

What makes it different.

01

Not another chat window

It carries whole workflows from request to review-ready output.

02

A managed workforce

unikode operates the platform and the workers. Your team directs the work, not the tooling.

03

No prompt engineering

Direct it in normal business language. No prompt writing, and no new system for your teams to learn.

04

Works across enterprise context

Documents, spreadsheets, PDFs, emails, recordings, dashboards, codebases, systems, and exports, from a single file to hundreds of gigabytes in a single pass.

05

Coordinates specialized workers

Research, analysis, software, workflow, drafting, QA, reporting, and delivery workers run together.

06

Builds the system around the work

Dashboards, trackers, review queues, and lightweight internal tools.

07

Produces review-ready outputs

Source-linked and structured, so review is quick and the next step is clear.

08

Keeps humans in control

Nothing reaches a client, a system, or the public without your approval.

Normal language in; reviewable work out 04 / 09
unikodeThe proof

Proof

Deployed and operating today.

This is a working platform, not a concept. unikode runs its own company on it, and live client work moves through it today.

The company

unikode runs on unikode.

  • Platform architecture, orchestration, agent workflows, and CI/CD were built through the system
  • Inbound requests become triaged, planned, executed, and validated work
  • 70+ automated pipelines and 400+ validation gates govern the operating model
A client, in depth

A firm-wide operating layer.

  • Java & Jebreil runs intake, matters, files, website/forms, marketing, SEO, and publishing on it
  • Complex legal workflows move through the same layer: discovery, meet-and-confer, referrals, litigation support
  • Attorney approval before anything reaches a client, a court, or the public
The base

Ten active client accounts.

  • Nine law firms and one national consumer brand
  • Each in an isolated, governed workspace with its own mailbox and records
  • Immigration packets, litigation support, research, and content delivered under review
Every claim on this slide traces to the platform's own records05 / 09
unikode The proof

Execution breadth

What the platform executes.

01

Mailbox to execution

Inbound requests become structured work items, plans, executed workflows, and review-ready drafts.

02

Legal operations

Discovery responses, meet-and-confer letters, referral reviews, immigration packets, attorney approval packages.

03

Business operations

Executive decks, competitive research, proposals, client onboarding, website updates, and publishing.

04

Engineering and platform operations

Issue triage, code review workflows, CI/CD, deployment guardrails, account provisioning, audit trails.

05

Knowledge and feedback

Client preferences, finalized artifacts, and corrections become reusable context for the next engagement.

06

Governance on every path

Source-linked outputs, deterministic validation, review gates, human approval before anything external.

07

The same loop, repeated

One intake, execution, and approval pattern, pointed at workflow after workflow as clients grow.

08

Why it matters commercially

Not a chatbot: a governed execution layer for high-value professional-services and enterprise work.

unikode carries the work; people direct, review, and approve 06 / 09
unikode The operating model

System flow

Messages and files become governed work.

unikode connects to the places work already lives, runs it through a managed operating layer, and returns review-ready deliverables.

01 / Intake

Messages and records

Messages
  • Mailbox
  • Teams
  • Slack
  • WhatsApp
  • Messaging UI
Files and records
  • Google Drive
  • OneDrive
  • Secure folders
  • Hosted files
02 / Private unikode servers

The operating layer

Agents execute with context, evidence, validation, and human approval gates.

01Context memory
02Knowledge graph
03Orchestration
04Managed agents
05Validation
06Approval gates
03 / Client delivery

Deliverables and review

  • Documents
  • Decks
  • PDFs
  • Sites/forms
  • Data packs
  • Any file type
Human review

Approvals, outcomes, and corrections feed the next run.

Connect the work once; improve every run after review 07 / 09
unikode The path

Commercial path

Start narrow. Scale across the operation.

The entry point is a free trial with real workflows. The expansion path is domain-agnostic: once the operating layer is connected, more work can move through it.

01 Connect

Free trial

Connect a live request lane, one message channel, and the files needed for real work.

02 Prove

Three free workflows

Run three review-ready workflows against the customer's actual messages, files, and systems.

03 Operate

Subscription

Move recurring work into the managed layer with source links, validation, and approval gates.

04 Expand

Scale across domains

Point the same operating pattern at the next domain once the first is proven.

Domains Legal Marketing Engineering Operations Procurement Finance Human resources
One operating pattern; many domains after proof 08 / 09

QA

Have questions? Reach out to agent@unikode.ai