Unlock the Power of AI
for Your Business.

Meet SI.OS, the SuperIntelligence Operating System that sits beneath every decision your business makes. Governed, sovereign, and running inside your own boundary — now deploying with a small number of enterprises. Your people move at AI speed without giving up control.

The real problem

AI is everywhere.
Control isn’t.

Your teams have ChatGPT, Copilot, and a dozen other tools. Not one of them knows your business, follows your policy, or keeps your data inside your walls. So the work that actually matters — the consequential decisions — still cannot be handed to AI. SI.OS changes that — one sovereign operating system beneath every AI action in your company.

What SI.OS is

One OS beneath every AI action.

Context. Action. Trust. Sovereign by design, across three layers.

OS

The Context Fabric

Your business, encoded — memory, retrieval, and inference that all run on your side of the line. Every action starts from what your company actually knows: your customers, your records, your rules.

MALA

Decision Governance

Anything consequential is measured against your policy before it is allowed to run, not after. Capability tokens scope what each action may touch, and the resulting audit trail is immutable and provable.

MAYA

Ambient Intelligence

An AI coworker for every employee, present in the flow of the working day. It drafts and decides within your boundary and has no route to anywhere outside it.

SI.OS across your org

Eight departments. One operating system.

The same governed intelligence runs across every function, with context and policy scoped to each one.

Revenue

Pipeline, quotes, follow-ups, forecasting.

Marketing

Campaigns, content, demand, attribution.

Finance

Reporting, approvals, AP, controls.

HR & People

Hiring, onboarding, policy, cases.

Legal & Compliance

Review, policy, evidence, risk.

Operations

SOPs, vendors, workflows, scheduling.

Customer Success

Onboarding, renewals, support, health.

Executive

Cross-org context, decisions, oversight.

Why SI.OS

Governed. Sovereign. Yours.

01

Inside your boundary

Deployment happens in infrastructure you already own. Your environment, your control, and no carve-outs to the rule.

02

Your data never leaves

Nothing is shipped out, and nothing you hold becomes training material for a shared model. Sovereign is the default setting, not an upgrade.

03

Policy before action

Governance runs ahead of execution rather than being pieced back together during an audit months later.

04

Mathematical proof

Consequential decisions are written down as immutable evidence you can verify — a proof, not a log line someone could edit.

Industries

Built for the floors where it counts.

Manufacturing

Inspection, downtime, and the paper trail that follows a defect to its root cause.

Healthcare

Documentation, intake, and authorisation — with patient data that never crosses the boundary.

Financial Services

Diligence, monitoring, and reporting where every conclusion cites the document behind it.

Restaurants & Hospitality

Ordering, reservations, and the calls that go unanswered at peak service.

B2B

Quoting, onboarding, and renewals across a long sales cycle with many hands on it.

Selected work

Six engagements, drawn to scale.

How we scope, staff, sequence, and measure a build — so you can see where yours would land before anyone quotes you a number.

These are illustrative engagement shapes, not delivered client work, and the figures below are scope rather than results. We do not publish client names or outcome numbers without written permission and something you can verify.

Support

01

Tier-one deflection agent

A support agent grounded in an existing help centre and ticket history, answering the top of the queue and handing anything uncertain to a person with the context attached.

What gets built

  • Retrieval over help centre and three years of resolved tickets
  • Confidence-gated handoff into the existing human queue
  • Weekly review loop over every escalated conversation

Stack

RetrievalEvaluation suiteZendeskWeb + in-product

Measured on

Deflection rate · Escalation accuracy · CSAT on resolved chats

Timeline
6 weeks to production
Team
1 engineer, 1 lead

Finance

02

Invoice intake and reconciliation

Extraction from mixed-format supplier invoices, matched against purchase orders, with everything below threshold routed to a review queue rather than guessed at.

What gets built

  • Document extraction across PDF, scan, and email body
  • Three-way match against the ERP with tuned confidence thresholds
  • Exception queue designed with the team who staff it

Stack

Document AIERP integrationReview queueAudit trail

Measured on

Straight-through rate · Extraction accuracy · Hours returned monthly

Timeline
8 weeks to production
Team
2 engineers, 1 lead

Sales

03

Inbound qualification line

A voice agent that answers on the first ring, qualifies against your criteria, books into the calendar, and writes the summary into CRM before the call ends.

What gets built

  • Sub-second first response held as a hard budget
  • Barge-in and interruption handling from the first build
  • Warm transfer to a human without losing context

Stack

Realtime speechTelephonyCRM write-backCalendar

Measured on

Answer rate · Qualification precision · Booked-meeting conversion

Timeline
7 weeks to production
Team
2 engineers, 1 lead

Operations

04

Field-ops assistant

A mobile client for technicians — job context, photo capture, structured reporting, and a model that drafts the write-up before they leave site.

What gets built

  • Offline-first capture that syncs when signal returns
  • Drafted write-ups a technician edits rather than authors
  • Supervisor review screen with override on every field

Stack

React NativeOffline syncVisionUsage analytics

Measured on

Report completion time · Data quality · Technician adoption

Timeline
12 weeks to production
Team
3 engineers, 1 designer, 1 lead

Governance

05

Policy-gated approvals copilot

A copilot for consequential decisions — discounts, credit, exceptions — where every proposed action is checked against written policy before it can run, not after.

What gets built

  • Policy encoded as checks the model cannot route around
  • Capability scoping per action, so reach is bounded by design
  • Immutable audit trail on every decision, approved or refused

Stack

Policy engineCapability tokensAudit logSSO

Measured on

Unattended-action rate · Policy violations caught pre-execution · Time to approval

Timeline
10 weeks to production
Team
2 engineers, 1 lead

Marketing

06

Answer-engine visibility programme

Tracking how a brand surfaces inside AI-generated answers, auditing the signals on site that drive it, and generating content against what the audit actually finds.

What gets built

  • Prompt panel tracked on a schedule across answer engines
  • On-site AEO and SEO audit with a ranked fix list
  • Optional read-only Search Console and Analytics connection

Stack

Answer-engine trackingSite auditGSC + GA4Content pipeline

Measured on

Share of answers citing the brand · Fixes shipped against the audit · Assisted pipeline

Timeline
4 weeks to first report
Team
1 engineer, 1 strategist

Frequently Asked Questions

Codesfarm is a full-stack AI studio. We design, build, and operate AI systems end to end, and we are the team behind SI.OS.

A SuperIntelligence Operating System: one governed layer that sits underneath every AI action taken in your company. It supplies the context, enforces the policy, and records the evidence, across three layers — Context Fabric, Decision Governance, and Ambient Intelligence.

Those are assistants that sit on top of your work and know nothing about your company. SI.OS is the layer beneath them — it carries your business context into every call, checks each consequential action against your policy before it executes, and keeps the whole thing inside your own infrastructure.

It deploys into infrastructure you already own and operate. Data is not sent out of your environment and is never used to train shared models. Sovereignty is architectural here rather than contractual.

Eight functions today — revenue, marketing, finance, HR and people, legal and compliance, operations, customer success, and the executive layer — all running the same governed intelligence with context and policy scoped per department.

It is deploying now with a small number of enterprises. Availability is deliberately limited while the early implementations are supported closely.

Roughly two weeks from kickoff to a working prototype. Production implementations typically run four to eight weeks once integration work is included.

Book a call. We will walk through where the consequential decisions in your business are being made today, and what it would take to put a governed layer underneath them.

By the numbers

End to end

Designed, built, operated

Across healthcare, manufacturing, financial services, hospitality, and B2B.

See the work

~2 weeks

Kickoff to working prototype

Production implementations run four to eight weeks including integration.

How we build

Published by Codesfarm.

Magnet

AI & answer-engine visibility.

Magnet is our AI and answer-engine visibility platform. It tracks how your brand turns up across AI-generated answers, audits the SEO and AEO signals on your site, and generates optimised content against what it finds.

You can optionally connect Google Search Console and Google Analytics, so your own search and traffic data sits inside the workspace and keyword analysis is grounded in what actually happened rather than an estimate. Those connections are read-only and entirely optional.

Let’s chat