Intelligence Without Limits
Ontilus designs and engineers bespoke AI operating systems for complex, multi-entity operators. We turn fragmented operational data into one live source of truth — and one engine that tells your leadership what to do next.
Net sales today
RM 428,650
▲ 6.2% vs target
Outlets reporting
33 / 33
All feeds healthy
Hourly sales vs target
last 12h
Decision engine
Engineering AI systems for operators across Malaysia & Southeast Asia
The problem
Most operators aren't short of information. They're short of a single place where it means something — before the week is over.
Today's friction
What we engineer toward
−70%
Manual reporting time
Live telemetry replaces outlet-by-outlet consolidation
+60–70%
Back-office efficiency
Automated invoice capture and coding leaves your team handling exceptions, not data entry
+3–6%
Revenue uplift
Demand forecasting, dynamic pricing and retention
+2–4 pts
EBITDA margin
Cost variance detection, less wastage, labour optimisation
These are the targets we engineer toward, based on comparable AI deployments at similar scale. They are directional, not guaranteed. We measure and validate against your own numbers during pilot before anything scales group-wide.
Capabilities
Live operational streams — transactions, inventory, labour, finance — unified across every legal entity and reconciled against your own close reports.
Demand forecasting, pricing optimisation and variance detection that run before the day starts — not after it ends.
It answers the daily why and recommends the next best action. A strategic partner in the business, not a static report.
Role-based access, entity-level isolation and audit-ready logging — designed from day one for regulated, multi-company groups.
The Ontilus platform
We don't hand over a dashboard and leave. We build the layer that sits between your operations and your decisions — on your data, in your entity structure, under your governance.
Applications
Command centers · Agents · Workflows · Executive views
Ontilus AI engine
Reasoning · Memory · Forecasting · Recommendation
Data intelligence layer
Identity graph · Telemetry · Analytics · Reconciliation
Infrastructure
Isolated VPC · Encrypted · Audit-logged · Regional
The systems we build
Every engagement is bespoke, but almost all of them resolve into these two — and they're designed to fuse into a single engine.
System 01
Real-time operations, AI decisioning and executive intelligence on one live surface — from the outlet floor to the board pack.
Net sales — today
RM 428,650
▲ 6.2% vs target
Guests
7,412
▲ 3.1% WoW
Average spend
RM 57.83
▲ 2.9% WoW
Outlets above target
24 / 33
9 need attention
Net sales by hour — group
Today · RM thousands · dashed line is target
Outlets needing attention
| Outlet | Entity | Sales vs target | Status |
|---|---|---|---|
| Bangsar Flagship | Entity A | −14.2% | Below |
| Mid Valley Kiosk | Entity A | −8.6% | Watch |
| Damansara Heights | Entity C | −6.1% | Watch |
| KLCC Terrace | Entity B | +11.4% | Ahead |
Food cost %
31.4%
▲ 2.1 pts vs target
Variance value
RM 18,240
This week, group
Price alerts open
7
3 need approval
Wastage logged
RM 3,910
▼ 12% WoW
Food cost % against target
By entity · target 29.3%
Supplier price drift
Detected in the last 7 days
Comparison matrix suggests switching 2 lines — est. RM 4,180/mo
SKUs tracked
1,284
Across 4 entities
Below PAR
18
6 critical
Stock value
RM 612,400
▼ 4.4% MoM
Auto-debits today
9,841
From POS sales
PAR level alerts
Ingredient stock auto-debits on every sale — alerts fire before the shortfall
| Item | Location | On hand | PAR | Status |
|---|---|---|---|---|
| Beef short rib | Central kitchen | 12 kg | 45 kg | Critical |
| Truffle paste | Central warehouse | 3 tub | 10 tub | Critical |
| Burrata | Outlet 12 | 8 pc | 14 pc | Low |
| Espresso beans | Outlet 04 | 22 kg | 20 kg | Healthy |
Transfers between entities post inter-company debit and credit entries automatically
Group revenue MTD
RM 9.84M
▲ 4.8% vs LM
Gross margin
64.2%
▲ 0.9 pts
Labour %
21.7%
Target 22.0%
EBITDA margin
14.6%
▲ 1.2 pts
Contribution margin by outlet
Top and bottom performers · month to date
Bangsar Flagship carries 2.4× the rent per cover of the group median — flagged for review
Labour cost % on shift
Live, from biometric clock-in · target 22%
Tomorrow's prep forecast
Auto-generated 04:00 · pushed to head chefs
Forecast accuracy last 30 days: 94.1% within tolerance
Kitchen throughput
| Station | Avg ticket time | Target | Status |
|---|---|---|---|
| Grill | 9m 12s | 10m | On pace |
| Wok | 7m 48s | 8m | On pace |
| Cold larder | 13m 05s | 9m | Bottleneck |
Morning briefing
Generated 06:00 · for Group Operations Director
Group is tracking 6.2% ahead of target on revenue, but gross margin is being eaten from two directions. Three actions are worth taking today.
Approve the poultry supplier switch
Chicken thigh is up 9.4% at Supplier 04 while Supplier 07 has held price for 11 weeks. Same spec, same lead time.
Est. impact +RM 4,180 / month · confidence high
Re-staff cold larder for dinner service
Cold larder is running 45% over target ticket time and is the single largest driver of dinner table turn delay across 6 outlets.
Est. impact +RM 2,600 / week · confidence medium
Review Bangsar Flagship lease terms
Contribution margin has sat below 10% for 4 consecutive weeks. Rent per cover is 2.4× the group median; the outlet is not a volume problem.
Est. impact structural · escalate to board
System 02
Unified customer intelligence and an engine that runs engagement on its own — so retention stops depending on who remembered to send the campaign.
A single 360° profile per customer, group-wide — one identity across every brand you operate.
Journeys that fire themselves, on time, every time — with consent tracked per customer, per channel.
External signal measured against internal return — so marketing spend is judged on contribution, not impressions.
Fused with the Command Center, operational and customer data become one predictive engine.
Ask the system
Your team already asks these questions. Today the answer takes three days and four spreadsheets.
›
How we deploy
We build outlet by outlet, entity by entity. Nothing goes group-wide until it reconciles against your own close reports.
Weeks 1–3
One entity · one POS estate
Weeks 4–6
Pilot entity + central kitchen / warehouse
Weeks 7–10
Including legacy and on-premise systems
Weeks 11–12
Every outlet · every legal entity
What makes it land
Standardise the taxonomy. One naming convention across every system before we integrate.
Appoint one champion. A single internal owner for data validation, not a committee.
Three metrics first. Teams learn sales vs target, labour on shift, and critical alerts. Everything else follows.
Security & governance
Multi-entity groups don't get to be casual about data. Separation, consent and audit trails are architecture decisions here, not settings we add later.
Transparent running costs
You'll know your monthly operating cost before you sign — inference, infrastructure and integration, itemised and sized to your actual transaction volume. Confirmed at technical scoping, not estimated after go-live.
TLS 1.3 in transit, AES-256 at rest, across every service.
Scoped by entity, brand and outlet. People see their scope, nothing else.
Hard separation between legal entities — not a filter on a shared table.
Full change history on every record and every access event.
Consent tracked per person, per channel. PII minimised by default.
Private VPC, regular key rotation, regional data residency.
Where we work
We're strongest where there are many locations, several legal entities, and data that has never been in one place.
Multi-outlet, multi-brand groups with mixed POS estates and central kitchens.
Inventory across channels, margin per SKU, and demand that moves weekly.
Scheduling, utilisation and compliance reporting under strict data handling.
Enrolment pipelines, cohort performance and cross-campus consolidation.
Utilisation, realisation and pipeline intelligence across practice groups.
Group reporting where every subsidiary runs a different stack.
Selected work
Named case studies are released as each client clears them for public presentation. Full walkthroughs are available under NDA on request.
Hospitality · Multi-entity
Live telemetry, recipe-level costing and a decision engine across a four-entity restaurant group.
Retail · Inventory
Forecasting and automated purchasing across a multi-channel retail estate.
Services · Automation
Invoice capture, coding and exception routing across separate legal entities.
Growth · Customer data
One profile per customer across several brands, powering automated retention journeys.
Questions
If yours isn't here, ask us directly. We answer scoping questions before there's a contract in sight.
Talk to usBespoke AI operating systems. In practice that means a live data layer over your existing systems, predictive engines on top of it, and an interface your team actually opens every morning — plus the automations that remove manual work underneath. We're not reselling a product; we architect and build for your entity structure.
A dashboard reports what happened. Our systems explain why it happened and recommend what to do about it, then execute the parts that can be automated. The difference shows up in the morning briefing: a ranked, costed list of actions instead of twelve charts and an interpretation problem.
Yes — including the awkward ones. Where a system has webhooks or an API we integrate directly. Where it's on-premise or legacy we deploy local sync agents and batch ETL. Most groups we work with run three or four different systems across their entities, and that's the normal starting point, not a blocker.
Three weeks to a live pilot on one entity, twelve to a group-wide system. We deliberately validate against your own close reports before scaling — it's slower on paper and far faster in reality, because nobody has to unpick a bad rollout.
You do. Your data stays in infrastructure scoped to you, with residency where you need it. Commercial terms on the codebase are agreed up front — we'll tell you exactly what you own before you commit, not after.
Monthly operating cost breaks into three lines: AI inference, cloud infrastructure, and integration middleware. We size all three against your actual transaction volume during technical scoping and give you the number before you sign — including how it grows as you add outlets.
Tell us what's slowing your operation down. We'll show you what the system would look like running on your data — before you commit to anything.
Kuala Lumpur, Malaysia · Serving Southeast Asia