NG  ·  Built in Lagos  ·  Infrastructure for the world
~95% of enterprise AI pilots never reach production

The Production Layer
for Enterprise AI.
From pilot to production,
inside your boundary.

Evaluation, guardrails, audit trails, and vendor-neutral model routing — designed to run inside your own boundary, so your data never has to leave it. Grounded only in your knowledge, cites every source, never invents. Battle-tested inside our own products.

Request a design-partner slot Read the security model →
Proof, not promises

The production layer already runs live inside our own products. Omos is what we're extracting from it — infrastructure any business can plug into.

3
products battle-testing the patterns
(Sydence + AI Kraft live · ExamSurf in build)
1
platform being extracted
from what already works
Running inside Sydence ExamSurf AI Kraft
The Guarantee

Three guarantees the
incumbents can't make.

Everything Omos does derives from these three. Together they're what lets a regulated buyer put production AI on top of us — and the exact ground the labs and clouds structurally won't hold.

01 · Sovereignty

Your boundary

Omos is designed to deploy inside your own cloud or tenancy, so sensitive data never crosses the boundary that owns it. The reason teams build in-house becomes the reason they buy Omos.

02 · Production

Production-grade by default

Evaluation, guardrails, audit trails, monitoring and cost control are the product's core — not enterprise add-ons. The exact 20% that kills DIY builds ships in the box.

03 · Neutrality

No vendor hostage

Vendor-neutral model routing with automatic failover across providers. Models change monthly; your system shouldn't have to. Omos is the stable layer over an unstable model market.

Two Doors, One Platform

Deploy it in your organisation,
or embed it in your product.

Same core. Same isolation. Same never-invents guarantee. One platform serving two shapes of business — pick the door that fits how you work.

Door 1 · Deploy

For organisations

Bring Omos in-house.

Give your team an AI that knows every policy, playbook and process you've written. Grounded in your own knowledge. Cites every source. Speaks the languages your team actually speaks.

  • Your own Omos workspace
  • Upload your knowledge — live in minutes
  • Answers only from what you know
  • Full audit trail (the Vault)
In build The engine runs in production today; the Deploy workspace is being built now. We're taking design partners for it.
Door 2 · Embed

For product teams

Embed Omos into your product.

Ship AI features to your users without building the plumbing. Plug in through the API, configure an adapter for your domain, and go live in days — presented as Omos AI by default, or under your own brand at the Enterprise tier.

  • API + SDK integration
  • Adapter framework per domain
  • "Powered by Omos AI" default · white-label on Enterprise
  • Isolation enforced per product
Live proof The same patterns are battle-tested inside Sydence and AI Kraft today.
One core · one trust layer · one platform. Whichever door you choose, the intelligence is the same.
A Day Inside Omos

What using Omos actually looks like.

One day, one team, one platform — seen through each door. Deploy makes the intelligence yours to use directly. Embed puts it inside the product your users are already in, presented as Omos AI.

Door 1 · Deploy · a Lagos studio

The team asks Omos directly. The intelligence is visible, and it belongs to them.

  1. 08:30Monday morning. Ops asks Omos what moved over the weekend. Three cited updates come back, pulled from the docs and threads the team already keeps — no hunting through channels.
  2. 09:45Client Zoom in 15. Ops asks Omos: "What's the current status of Titan and any blockers?" Three lines back, cited to the last standup notes and the retro. Pasted into meeting notes.
  3. 11:20A designer asks in Yoruba about their IP policy for a collab. Answer arrives in Yoruba, sourced to the English policy doc. Ten seconds.
  4. 14:15Unprompted, a Slack ping from Omos: "Orbit SOW is unsigned. Kickoff Wednesday." Nobody asked; the Watchtower noticed.
  5. 16:00A new hire asks how expenses get approved. Omos answers from the finance policy, quotes the exact clause, and links the doc. No one had to stop what they were doing.
  6. 17:45Someone asks what the team agreed on Titan's scope last month. Omos answers with the decision and its source — every answer logged in the Vault, so there's always a record.
Users are aware of Omos. It's their AI.
Door 2 · Embed · inside a product

The intelligence arrives labelled Omos AI — a trust badge users learn to recognise. (White-label available at Enterprise.)

  1. 08:45A studio lead opens Sydence. An Omos AI panel greets her by name and highlights three things: an overdue task on Titan, a client update draft waiting for review, and a new idea overlapping past work.
  2. 10:00Reviewing a brief. She highlights a section and asks Omos AI: "What did we learn from Titan's retro that applies here?" Three specific learnings, cited. One goes in the brief.
  3. 11:30Standup time. Omos AI has already drafted her standup from yesterday's activity — closed tasks, comments, pipeline moves. Two edits and send. Fifteen seconds, not five minutes.
  4. 13:45A designer types into the Omos AI panel: "Move Orbit to In Progress and assign it to Ade." Done. Update posted, Ade notified, Slack pinged. She never opened the pipeline view.
  5. 15:20Client meeting prep. She asks Omos AI: "Draft a project update email for Compass based on this week's activity." Right tone, right specifics, honest about the current blocker. 90 seconds of editing, send.
  6. 17:30By end of day she's used Omos AI a dozen times without breaking flow. Every answer cited, every action logged. The badge means what it says.
Omos AI shows up as itself — a mark of trust across every product it powers.
Same intelligence. Same trust guarantees. Same platform underneath. Only the point of contact changes.
The Gap in the Market

Every team deserves AI that
actually knows their world.

Generic AI Knows Nothing

ChatGPT and generic AI assistants have no idea what your product does, who your users are, or what your domain requires. Users explain context every single time.

Enterprise Tools Lock You In

Platforms like Glean run six figures a year, serve only internal employees, and standardise you onto their single stack. Powerful for a Fortune 500 — rigid and overbuilt for a team that needs to move fast.

AI Locks You In

Building on any single AI vendor means surrendering your data, your pricing control, and your product independence. Switching costs are brutal.

"Omos closes all three gaps — at once."
Why Now

The models finally got good enough —
and every product now needs them.

01

AI models are now capable and affordable enough to embed in any product — a threshold that simply didn't exist two years ago.

02

Users now expect contextual intelligence inside every tool they use. A product without it feels broken. Every team is scrambling to add it.

03

The incumbents are built for one shape of buyer — large, internal, single-vendor. The product teams and fast-moving enterprises that need this most have no production layer built for them — until Omos.

The Platform

Ten engines.
One platform.

Five engines that think. Two that act. Three that make Omos safe to deploy in a regulated business. Every one is a named, ownable part of the product — no black boxes.

Your Product
→
Omos Integration API
→
Core Intelligence Engine
→
Product Adapter
→
Isolated Knowledge Base

Answers are grounded only in your product's knowledge and cited to source — Omos never invents. Each product's knowledge is fully isolated, and your data never trains shared models. Enterprise deployments add dedicated hosting, audit trails, and a compliance roadmap. Our data & security approach →

01 Intelligence · five engines that think
The Reading Room

It learns your product

Feeds on your product's documents, workflows and data — and only yours — so it understands your world, not the internet's.

Live
The Brain

It answers, honestly

Replies in plain language, grounded only in what your product actually knows, and cites its source. If it doesn't know, it says so — it never invents.

Live
Quality Dept

It keeps knowledge healthy

Watches for gaps and contradictions in the background — the foundation is running today, and we're building it toward a live score of how healthy your product's knowledge really is.

In build
Translation Bureau

It speaks your languages

English natively today, with Yoruba and Hausa rolling in next — Igbo, Swahili, Zulu and Twi after that. Native reasoning, not translated English. The African-language layer most AI overlooks.

In build
The Vault

It remembers, defensibly

Every action is logged today. We're building toward a permanent, tamper-proof record of every answer too — so you'll always have proof of what was known, and when.

Live
02 Action · two engines that do
The Hands

It acts, not just answers

Turn intent into work. Omos creates tasks, updates records, drafts documents — validated at every step, reversible where it can be, and fully audited. Six live actions today, more per adapter.

Live
The Watchtower

It watches while you work

Runs quietly in the background — daily digests, smart alerts on blockers and deadlines, anomaly detection on unusual patterns. Answers arrive before users think to ask.

In build
03 Trust · three engines that make it enterprise-grade
The Switchboard

It routes without lock-in

Every request goes to the best-fit AI model, with automatic failover across providers. Your product doesn't go dark because one lab had a bad day. Vendor-neutral in architecture, not just marketing.

Live
The Gatekeeper

It refuses what it should

Input sanitization, prompt-injection defense, PII redaction, action re-validation. The engine that turns "trust us" into architecture a procurement team can actually approve.

In build
The Registrar

It respects your rules

Retention windows, legal holds, data-subject requests, audit exports. The controls that make Omos safe to deploy in a regulated business — designed to align with NDPR, GDPR, and SOC 2.

Roadmap
Signature Feature In build

A live score for your
product's intelligence.

Think of it like a credit score for what your product knows — a single number from 0 to 100. But it does more than grade you: it shows exactly what's dragging the score down, and what to do to raise it.

The signals it grades on are already tracked inside our engine today; we're building the score itself out now. When it lands, it turns Omos from a tool people use occasionally into infrastructure a team depends on — every lead who sees the score immediately asks, "how do I get it higher?"

0 – 100 Knowledge
Health
  • Coverage how much of what your team asks it can answer
  • Consistency contradictions across your knowledge
  • Freshness how up to date your knowledge is
  • Depth how thoroughly each topic is covered
  • Accessibility availability in your team's languages
The Architecture

Plug in. Adapt. Go live.

This is the developer experience we're building toward. The engine already runs inside our own products today — the self-serve SDK and adapters below are next on the roadmap.

1

Connect Your Product

Connect through the Omos SDK — the same integration path we use across our own products today.

// Omos SDK init
import Omos from '@omos/sdk'
 
const client = new Omos({
  apiKey: process.env.OMOS_KEY,
  product: 'your-product-id'
})
2

Configure Your Adapter

Define what Omos knows, what it can do, how it speaks. Your domain. Your rules.

knowledge_sources:
  - docs/
  - api/schema
actions:
  - create_task
  - draft_document
tone_rules:
  - concise
  - professional
3

Go Live with Intelligence

Omos is live in your product — answering, acting, monitoring, and improving — invisibly, under your brand.

⬤  Your Product — AI Panel
What's blocking the client project?
3 tasks are overdue on the Titan project. The design review scheduled for yesterday was not completed. Want me to reschedule?
Yes, set it for tomorrow 10am.
Done. Calendar updated and team notified.
Designed to take a new product live in under 48 hours.
Watch Omos live inside a product 60-second demo · coming soon
Built with Omos

Live in production.
Powering PegBit's own ventures.

Studio Operations Intelligence ● Live

Sydence

PegBit's studio operating system. Drafts SOWs, moves pipeline cards, flags blocked projects, and adapts to each team member's role and work style. The intelligence powering it is what Omos is being extracted from.

→ Creates tasks and drafts documents
→ Flags project issues proactively
→ Adapts to each team member
→ Knows every studio policy
sydence.com  ↗
Education Intelligence ◐ In build

ExamSurf

Nigeria's JAMB and WAEC exam prep platform. Generates fresh questions, explains every concept, tracks each student's weaknesses, and adapts every session in real time. Runs on the same intelligence patterns being extracted into Omos.

→ Personalised for every student
→ Fresh questions generated on demand
→ Proactive study reminders
→ JAMB + WAEC syllabus-aware
examsurf.com  ↗
Case Snapshot · Sydence
The problem

A studio drowning in scattered docs, stalled pipeline cards, and status no one could see at a glance.

→
What Omos does inside it

Drafts SOWs from context, moves pipeline cards, flags blocked projects, and answers "what's the status of X?" in plain language.

→
What it enabled

An operating system that runs itself — the team acts on insight instead of hunting for it.

The Team

Two founders.
Building from Lagos, Nigeria.

Oluwadamilola Oladunni, Founder & CEO of PegBit Technologies OO
Founder & CEO · PegBit Technologies

Oluwadamilola Oladunni

An AI-native engineer on a mission to close the gap between AI demos and AI that survives production. He founded PegBit Technologies to build that missing layer for businesses across Africa and beyond — and Omos is the infrastructure the mission runs on. He stays hands-on across the studio and every venture built on the platform.

Ships production AI, not demos Multiple live ventures shipped Hands-on technical founder

Full founder background, the wider team, and PegBit's track record live on the parent company site.

See the team & track record at PegBit  →
AA
Co-founder & Head of Engineering · PegBit Technologies

Alexander Akinyomola

Leads the engineering core building Omos — the platform extraction, the delivery unit, and the technical standard everything ships against. He joined PegBit as co-founder to lead engineering into the platform's next phase: turning the intelligence running inside Sydence and ExamSurf into infrastructure any business can deploy.

Leads the Omos platform build Heads the Lagos engineering core
Backed by

PegBit Technologies Ltd

Omos is a venture of PegBit Technologies — an AI-native engineering studio in Lagos running a studio-and-ventures model. The studio's own products are the proving ground for Omos — the platform is battle-tested at real scale before it ever reaches an external customer. Foundation meets Frontier.

Visit pegbitstudio.com  →
Sydence ● Live ExamSurf ◐ In build AI Kraft ● Live Omos ◆ The layer beneath
Why Omos

Built different.
Open by design.
Built to last.

Feature Generic AI Glean / Ada Build in-house Omos
Domain-specific intelligence ✗ Partial ✓ ✓
Knowledge isolation per product ✗ ✗ Partial ✓
Per-user personalisation ✗ Partial Partial ✓
Proactive monitoring ✗ Partial Partial ✓
Vendor-neutral LLMs ✗ ✗ Partial ✓
White-label available (Enterprise tier) ✗ ✗ ✓ ✓
Pricing philosophy Cheap, limited $350K+/yr Months of eng + upkeep Enterprise-grade, no six-figure floor
Emerging-market & local context ✗ ✗ ✓ ✓
Native African-language answers ✗ ✗ ✗ ✓
Never invents · cites every answer ✗ Partial Partial ✓
Knowledge health scoring ✗ ✗ ✗ In build
Time to production Instant, shallow Quarters + $$$ 6–18 months + a platform team Days
The Vision

A foundational platform
powering an entire ecosystem.

Omos isn't one more app — it's the production layer that takes enterprise AI from pilot to production, inside the customer's own boundary. It already runs live beneath our own products, and every integration makes it smarter and harder to replace. We start where a security review decides the deal — and scale from there.

$7.2B
Glean's valuation — the market for AI that understands your context is already proven, and enormous.
3
of our own products already battle-testing the platform (two live in production) — proven before it ships to anyone else.
95%
of enterprise AI pilots die before production — the exact gap Omos is built to close.

Glean proved enterprises pay enormous sums for AI that understands their context. But Glean serves only internal employees, only one organisation, and only at enterprise pricing.


Omos is built to serve the product teams and enterprises Glean cannot reach — the same class of intelligence, open across model vendors, adapted to any domain, and designed to deploy in days.


Our buyer is the organisation whose AI stalls at the security review — where data residency, auditability and vendor independence decide whether anything ships at all. That describes regulated enterprises and serious product teams on every continent, and almost nobody builds for them. We don't pitch a demo; our own live products already run on this layer. Built in Lagos, designed for the world — we move fast, ship real, and widen the moat with every integration.

Revenue Model

Per-product monthly subscription. Predictable, recurring ARR that compounds as each product scales its query volume.

Defensibility

Proprietary adapter pattern creates deep integration stickiness. Domain-specific knowledge bases produce network effects per vertical.

Expansion Path

Own products → in-boundary enterprise deployments → self-serve platform & region-first models. Each phase widens the moat.

The Market

Glean proved the demand.
It serves a fraction of it.

The production-layer opportunity was never only a Silicon Valley story. The buyer we build for is the organisation whose AI stalls at the security review — where data residency, auditability and vendor independence decide whether anything ships. That buyer exists in every market, and almost nobody builds for them.

Why in-boundary wins

Wherever data protection is enforced seriously, the same question decides the deal: where does our data actually go? Answering it with architecture rather than assurances is Omos's first guarantee — and the reason a regulated buyer can say yes at all. We build from Lagos, inside one of the fastest-growing technology regions in the world, and serve that buyer wherever they are.

Where we build from
$41.8B
projected Middle East & Africa SaaS market by 20301
$3.2B
raised by African startups in 2024 — the products that need this layer2
~13k
startups registered under Nigeria's Startup Act — the most in Africa3
5
Nigerian unicorns already — a proven, investable builder ecosystem4
How we go to market
01 · Wedge

Land organisations whose AI is blocked at the security review, entered through Deploy and studio engagements — starting with the businesses closest to us, where trust and integration move fastest.

→
02 · Expand

Product studios, edtech and fintech teams underserved by incumbent pricing and unsupported in their own languages — reached through PegBit's network first, then outward. Every integration compounds stickiness.

→
03 · Platform

Open self-serve, add a marketplace of domain adapters, and move up into fine-tuned, region-first models — the durable infrastructure moat.

Sources: 1. Grand View Research, MEA SaaS market · 2. Partech Africa Tech VC Report 2024 · 3. Nigeria Startup Portal (Technext) · 4. Forbes Africa

The Roadmap

Prove it, then build it right.

We're not shipping a half-built platform and hoping. We're hardening Omos inside our own products first, letting real usage tell us what to build — then extracting it into the standalone platform. This is how durable infrastructure gets made.

● Now
Phase 1

Prove & extract

Battle-test the intelligence patterns inside our own live products, where we control the feedback loop. Extract those patterns into Omos — a standalone platform any business can plug into.

  • Sydence's intelligence layer live in production
  • ExamSurf onboarding onto the same core
  • Extracting the shared patterns into Omos
  • Opening the first design-partner slots — two per door
Phase 2

Extract the platform

Turn the proven engine into a standalone product — the SDK, adapters, and onboarding an external team can use without us in the room.

  • Self-serve SDK & integration API
  • Adapter framework per domain
  • Per-product knowledge isolation
  • Design partners live in production
○ Then
Phase 3

Open to the world

Open Omos to any product team, with the pricing and reliability layer to match — the infrastructure play in full.

  • Public availability & pricing
  • Enterprise deployment & compliance
  • Marketplace of domain adapters
  • Fine-tuned, Africa-first models

Building something Omos could power, or want to back what we're building?

Become a design partner
Design Partners

Build Omos with us.

We're looking for a small handful of design partners — one for each door — to shape the platform with us before it goes wide. Not beta testers. Strategic collaborators, generous terms, real influence on what gets built next.

What you bring
  • A real business, real users, a real problem Omos could solve
  • Time — a weekly conversation with our founder and engineers
  • Honest feedback, on time, on the record
  • Willingness to be a public case study when we launch
What you get
  • 6–12 months on generous terms (free or heavily discounted)
  • Direct line to the founder and engineering — your bugs jump the queue
  • Roadmap influence — you shape what gets built next
  • Founding-partner recognition when we go public
Deploy design partner

For organisations

An organisation deploying Omos for your own team's day-to-day. You upload your knowledge, we help you get value fast; we get real usage inside a live team, and one clear story of what "Omos in-house" looks like.

Ideal: an agency, mid-sized firm, NGO, or professional-services team — Africa or beyond.
Embed design partner

For product teams

A product company integrating Omos into a product you ship to your own users. You get help getting live and priority DX support; we get real API/SDK feedback under real load, and a launched integration to point to.

Ideal: an edtech, fintech, agency SaaS, or vertical B2B tool — Africa or beyond.
Best fit if
B2B — Africa or global Real users, real workflow Willing to give hard feedback Influence in your niche

Two or three slots per door. Deep engagement, not scale.

Apply as a design partner