Enterprise Cognition Platform

The Era of Enterprise Cognition Is Here.

Archisus connects your data where it lives, predicts what happens next, recommends the best action and checks every decision against your business rules before anyone acts on it. Every answer traceable. Every decision defensible.

Book a DNA Audit How It Works

Built for High-Stakes Sectors

Energy & Nuclear Government & Smart Cities Construction & Mega Projects Healthcare & Life Sciences
Who We Are

We Are Architects of Intelligence.

Archisus is not just a software company - we are architects of intelligence. A team of engineers, knowledge scientists, and domain strategists dedicated to bridging the gap between raw institutional knowledge and auditable artificial intelligence.

Founded on the belief that AI should adapt to the business - not the other way around - we empower organisations to encode their best expertise into governed digital assets that grow with the business and stay within its rules.

Knowledge Engineering

OWL · RDF · SHACL

AI Architecture

LLM · GNN · Fine-Tuning

Domain Expertise

Energy · Gov · Health

"To liberate human potential by automating the complex, cognitive tasks that slow down innovation."

Archisus Archisus Mission
6
Industries
2wk
First Results
100%
Rule-checked outputs
100%
Traceable outputs
2 Weeks
DNA Audit turnaround
47
Logic gaps found in one audit
Rules-first
Every output validated
The Problem

Your Operations Run on Certainty. Your AI Runs on Probability.

Across high-stakes sectors, the cost of an AI error is not a bad recommendation - it is a regulatory violation, an unplanned shutdown, or a patient harm event. Generic language models were never built for this.

01

Probabilistic output in a deterministic world.

A language model outputs the statistically likely answer - not the correct one. In nuclear safety, procurement compliance, or clinical decisions, "likely" and "wrong" are the same thing. Your industry does not run on plausible text.

Consequence: regulatory non-compliance, unsafe operating decisions, litigation exposure.

02

No traceable logic. No accountability.

When a regulator or auditor asks why the AI made that call, "the model said so" is not an answer. A black-box recommendation is a liability dressed as a feature. Without a traceable decision chain, you cannot defend, audit, or repeat any output.

Consequence: failed audits, inability to certify AI-assisted decisions, reputational risk.

03

Your operating rules live in documents, not logic.

Decades of safety procedures, compliance standards, and business rules exist as PDFs, wikis, and tribal knowledge. Generic AI reads them. It cannot enforce them. The moment context shifts or a document is out of date, the AI has no way to know - or care.

Consequence: institutional knowledge unused, AI acting on stale or contradictory rules.

04

Cross-system insight means a migration project. Or it used to.

Critical data lives in SAP, SCADA historians, and ERP monoliths. Getting AI to reason across all of it has traditionally meant moving petabytes of sensitive operational data to the cloud - a multi-year programme with security, compliance, and operational risk at every step.

Consequence: AI projects stall on data access, insights arrive years late, budgets consumed by plumbing.

Methodology

Enterprise Cognition: Facts, Rules, and Action — Connected.

Most AI retrieves. Ours reasons. Archisus builds a neuro-symbolic architecture on top of what you already own — a governed ontology layer, a constraint-enforcing reasoning engine, and a federated reach that queries your SAP, historians, and ERP in place. No migrations. No black boxes. Every output traceable to its source rule.

1

Map Your Business DNA

Not a database. A reasoning substrate.

We construct an OWL ontology — a machine-readable model of your business concepts, rules, hierarchies, and relationships. Unlike a vector store or a flat knowledge base, an ontology enforces logical consistency: your AI knows that a Purchase Order requires an Approved Supplier, and that approval requires a valid Compliance Certificate. This becomes the cognitive backbone of your Digital Expert.

OWL Ontology Knowledge Graph Business Rules
2

Connect Your Digital Expert

Non-compliant answers blocked before they reach you.

Your Digital Expert does not rely on the model behaving correctly - it reasons against your ontology using SHACL constraint validation before any output is produced. Every response is checked against your encoded business rules. Non-compliant outputs are rejected structurally. The result is an AI whose every output is checked against your governance policies.

SHACL Validation Constraint Reasoning Pre-release Validation
3

Deliver Expert-Level Intelligence

Every decision, traced to a knowledge node.

The Digital Expert runs a continuous Perceive → Reason → Act → Validate loop. It ingests live operational data, applies ontology-constrained reasoning, and executes actions inside your connected systems — ERP, data warehouse, SCADA. Every output is logged against a full, human-readable audit trail that traces each decision back to the exact ontology rule that produced it.

Agentic Loop ERP / DWH Integration Compliance Audit Trail

The Technology Chain

Business Data Sources
OWL Ontology Layer
SHACL Constraint Engine
AI Reasoning Engine
Auditable Action & Output

Why this is different

Generic AI / RAG
Archisus Digital Expert
Knowledge Source
Unstructured text chunks
Formal OWL ontology
Validation Layer
None
SHACL constraint enforcement
Auditability
Black box
Every decision traceable
Hallucination Risk
Uncontrolled
Blocked by rule validation
Domain Adaptation
Prompt engineering
Ontology-native reasoning
What the platform does

See. Predict. Decide. Govern.

Archisus is more than a guardrail. It gives your teams one view of the operation, predicts what happens next and recommends what to do about it, and makes sure every one of those decisions is provably within your rules.

See

One operational picture

Your ERP, asset, sensor and document data read in place and joined by meaning, with the KPIs that matter monitored continuously and alerts raised before a threshold is crossed, not after.

Federated data, no migration KPI monitoring Proactive alerts
Predict

Predictive analytics in business context

Forecasts of equipment failure, demand, delays and risk, judged against the specification, contract or regulation they affect, so a prediction comes with what it means for the business.

Failure & demand forecasting Anomaly detection Risk scoring
Decide

Guided decision-making

The next best action, ranked and explained. Test options with what-if scenarios before you commit, and let the optimiser find the best schedule, stock level or allocation within your constraints.

Next best action What-if scenarios Optimisation
Govern

Every action within your rules

Every prediction, recommendation and action is checked against your rules before it is released. Anything that breaks one is blocked and escalated, and each decision is recorded with the rule and data behind it.

Rules checked before release Audit trail Human escalation

ROI calculator

What would it be worth to your organisation?

Pick your industry, adjust a few numbers you know, and see an estimate of the annual value across all four pillars. Everything runs in your browser.

Estimate your ROI
The Architecture

Three Layers. One Reasoning Machine.

The Archisus platform is not a single product - it is a three-layer cognitive infrastructure that transforms raw enterprise data into governed, auditable intelligence.

01

The Constitution

Ontology Layer

An OWL knowledge graph encodes your business entities, rules, and relationships as machine-readable logic. Not a keyword database - a formal model of how your domain works. This is what your AI reasons against, not what it searches through.

OWL 2 ontology design Business rule formalisation Concept hierarchy & taxonomy
02

The Engine

Reasoning Engine on Your Graph Store

The Archisus engine runs OWL 2 inference, SHACL validation and rules, and query-based rules - SPARQL, or Cypher through neosemantics on Neo4j - over your knowledge graph, persisted in the graph store you already use: AWS Neptune, Ontotext GraphDB or Neo4j. Every output is checked against your rules before it leaves the system.

OWL 2 inference & consistency checks SHACL validation & rules Runs on Neptune · GraphDB · Neo4j
03

The Reach

Federated Data Layer

Your data stays where it lives. The federated layer connects SAP, SCADA historians, ERPs, and document stores via semantic adapters - querying each in place without migration. Cross-silo intelligence without the integration project.

Zero-migration connectivity SAP / SCADA / ERP adapters Cross-domain semantic join

Together, these three layers form an enterprise-grade cognitive infrastructure that runs inside your security perimeter, on your cloud, with full data sovereignty.

Runs on: AWS Neptune · Ontotext GraphDB · Neo4j

Explore the platform in depth →

Connectors

Connects to the systems you already run

The federated layer reads your ERP, asset, engineering, clinical and data platforms in place, through their standard APIs, so the data stays where it is and only query results move, inside your security perimeter.

  • S/4HANA · ECC · PM
  • Fusion · E-Business Suite
  • Microsoft Dynamics 365
  • Salesforce
  • IFS
  • Snowflake
  • Databricks
  • Google BigQuery
  • Redshift
  • Synapse
  • Microsoft Fabric
  • PostgreSQL
  • Microsoft SQL Server
  • Database
  • Apache Kafka
  • Microsoft SharePoint
  • Google Drive
  • Jira
  • Confluence
  • Maximo
  • AVEVA PI System
  • OPC UA (SCADA and historians)
  • DeltaV
  • Esri ArcGIS
  • Autodesk Revit · ACC
  • iTwin · ProjectWise
  • Primavera P6
  • Aconex
  • Procore
  • Epic (FHIR)
  • Oracle Health (FHIR)
  • HL7 FHIR
  • Vault
  • Neptune
  • Ontotext GraphDB
  • Neo4j
  • Google Cloud

Logos are trademarks of their respective owners and are shown to name the systems Archisus connects to; they do not imply endorsement.

Custom AI

AI That Knows Your Business. Not Just Language.

We design, train, and deploy AI models built entirely around your domain - your rules, your data, your constraints. Not fine-tuned copies of someone else's general model.

Custom AI Architecture

We don't retrofit. We architect from your domain up.

Every engagement starts with your domain model - entities, relationships, and rules encoded into a governed ontology before a single model is selected or trained.

  • Domain ontology design & validation
  • Architecture selection: LLM, GNN, or hybrid
  • Knowledge-grounded model specification

Domain Training & Fine-Tuning

Your data. Your language. Your domain.

Foundation models fine-tuned on your proprietary operational data, aligned to your ontology, and validated against SHACL constraints - so outputs stay within your governed boundaries.

  • Proprietary dataset curation & preparation
  • Supervised fine-tuning & RLHF alignment
  • Ontology-constrained output validation

Production AI Development

From prototype to production without the gap.

End-to-end delivery: API integration, secure infrastructure, performance monitoring, and continuous retraining pipelines - deployed within your security perimeter, not ours.

  • On-premise or private cloud deployment
  • CI/CD pipelines for model lifecycle management
  • Monitoring, drift detection & retraining
Discuss Your AI Requirements
Knowledge Base

Governed AI, explained in plain English

Short reads on knowledge graphs, ontologies, semantic layers and graph databases, and how they make AI follow your business rules.

All articles →
Why It Works

The Difference Is in the Architecture.

Generic AI generates text and hopes it is correct. Archisus validates every output against your encoded business rules before it leaves the system. Here is what that looks like in practice.

Same question. Completely different answer quality.

Generic AI / RAG

"Supplier ACME-12 may have compliance concerns. You should verify their certification status before proceeding with this order."

Archisus Digital Expert

"Rule 47.3 - Supplier ACME-12 blocked: ISO 9001 certificate expired 3 days ago. PO-2024-887 halted pending re-certification. Compliant alternative: Supplier ACME-07 (cert valid until 2027-03)."

2

Weeks

To map your full knowledge architecture

Every

Output checked

Validated against your rules before release, not prompted

47

Logic gaps

Found in one compliance audit, invisible before

100%

Traceable

Every decision tied to a source rule

Book a DNA Audit for your team
How We Engage

From Zero to Enterprise Intelligence in Three Stages.

We don't sell a licence and walk away. We start with a deep diagnostic, prove value fast, then scale across your organisation.

01
2 Weeks

Business DNA Audit

We map your knowledge landscape end-to-end. In two weeks we surface every critical reasoning dependency, broken data link, and governance gap - and deliver the ontology backbone model that will fix them.

Knowledge dependency mapping
Data link & governance gap report
Draft ontology model & use case roadmap
02
4–6 Weeks

Focused Pilot

One live Digital Expert targeting a single high-impact process - procurement, compliance, maintenance, or reporting. It runs against your real data, enforced by your ontology. You see measurable results before committing to full rollout.

One production-grade Digital Expert
Live data integration & SHACL validation
ROI baseline & full audit trail from day one
03
Ongoing

Enterprise Expansion

The ontology becomes a company-wide cognitive asset. We expand domain coverage, connect additional systems, and deploy further Digital Experts - each inheriting the same governed reasoning layer. Your AI estate grows without growing your risk.

Multi-domain ontology expansion
Fleet of governed Digital Experts
Centralised governance & compliance layer
Start with a DNA Audit

What the DNA Audit delivers →

Where We Deploy

High-Stakes Sectors. Deterministic AI.

We don't build generic AI and apply it to industries. We encode sector-specific physics, regulations, and operational constraints into governed ontologies - then reason over them. Here is where that matters most.

Energy & Nuclear

The Safety Contract

In a nuclear environment, "likely" is unacceptable. You need certainty.

  • Reactor physics and safety procedures encoded as a governed knowledge graph
  • SHACL governance layer blocks any recommendation that violates the safety ontology
  • Every answer traceable to rules and evidence - ready for regulator scrutiny

Outcome: Faster regulatory reporting, safer procedure guidance, anomaly triage with quantified confidence bounds.

Explore this sector →
Oil & Gas / Petrochemicals

Deterministic Asset Integrity

Predictive maintenance predicts failure. Archisus predicts consequences and compliant actions.

  • Federated query across SCADA, SAP, Maximo, and inspection records - data stays in place
  • Kalman filtering fuses noisy sensor signals into best estimates with confidence bounds
  • Automatic HSE and permit-to-work constraint checks before any action is authorised

Outcome: Fewer unplanned shutdowns, cross-silo insight in weeks, every decision explainable end-to-end.

Explore this sector →
Power & Utilities

The Cognitive Grid

A smart grid is useless if it doesn't have a brain. Sensors everywhere - alerts understood nowhere.

  • Topology graph models nodes, lines, and substations with ConnectedTo / Feeds / ConstrainedBy relations
  • Root-cause reasoning traces upstream causes and suppresses downstream noise to isolate the true fault
  • Automated dispatch generates work orders, checks parts, and schedules crews within encoded safety rules

Outcome: Faster restoration, fewer truck rolls, higher reliability - with auditable decisions and operator-ready explanations.

Explore this sector →
Government & Smart Cities

The Reasoning Twin

Your regulatory framework is a knowledge graph waiting to happen.

  • Building codes, zoning rules, and procurement policy encoded as machine-readable constraints
  • Permit applications validated and regulatory conflicts flagged before they enter the queue
  • Every approval decision routed through the correct chain with a full, auditable rationale

Outcome: Faster approvals, zero regulatory ambiguity, and a full audit trail on every public decision.

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Construction & Mega Projects

Federated Project Intelligence

Your project is a set of interlocking constraints. Your AI should reason over all of them, simultaneously.

  • Single reasoning layer across BIM, contracts, procurement, and scheduling - queried in place
  • Design compliance verified against live regulation before drawings reach the site
  • Material conflicts and dependency clashes surfaced with a traceable explanation, not a flag

Outcome: Fewer rework cycles, compliance confidence before ground breaks, and no cross-silo blind spots.

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Healthcare & Life Sciences

Clinical Intelligence Engine

Clinical pathways are logic. Formulary rules are constraints. Your AI should enforce both, not guess at them.

  • Treatment protocols, drug formularies, and patient-safety rules encoded as SHACL constraints
  • Live patient data cross-referenced against treatment logic - contraindications blocked structurally
  • Every clinical recommendation tied to the exact protocol rule that produced it

Outcome: Safer prescribing, faster clinical decisions, and a traceable rationale that satisfies auditors and clinicians alike.

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Retail & Consumer Goods

Precision Commerce Intelligence

Your sales data tells you what happened. Archisus tells you why - and what to do next.

  • Demand patterns, supplier constraints, and pricing rules encoded as a unified knowledge graph
  • Inventory optimisation governed by explicit business rules - no black-box recommendations
  • Customer behaviour modelled as ontology-linked profiles for traceable, explainable personalisation

Outcome: Reduced stockouts, higher margins, and decisions that merchandising teams can audit and trust.

Explore this sector →
Join Our Team

We Are Hiring

Help us build the future of enterprise intelligence. We are looking for exceptional talent to join our mission.

Business Development Executive

Europe & MENA

Drive our expansion into the European, Middle Eastern and North African market. We are looking for strategic thinkers with a proven track record in B2B enterprise software sales and a deep understanding of the EU and MENA tech landscape.

Machine Learning & AI Engineers

Remote / Hybrid

Build the next generation of Digital Experts. We are on the lookout for talented engineers proficient in Python, TensorFlow/PyTorch, and LLM fine-tuning to solve complex industrial problems.

Let's Start

The DNA Audit Is Your First Step. And Your Lowest Risk.

In two weeks we map every critical reasoning dependency, broken data link, and governance gap in your current AI or data workflow. You leave with a draft ontology model, a prioritised use case roadmap, and a clear decision on whether - and how - to proceed. No commitment beyond the audit.

Knowledge architecture map

Every logic dependency, data relationship, and constraint your AI needs to reason correctly - visualised and documented.

Gap & risk report

Broken data links, contradictory rules, and governance gaps that are invisible today - surfaced and prioritised by business impact.

Draft ontology & pilot roadmap

A working ontology model for your highest-priority domain, plus a ranked shortlist of pilot use cases with estimated ROI and delivery timeline.

[email protected]

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2-week engagement · Fixed scope · No ongoing commitment required

ROI calculator