Generic AI retrieves. Archisus reasons. We encode your business rules, relationships, and constraints into a governed ontology - then federate it across every data source you own. Every answer traceable. Every decision defensible.
Trusted by Industry Leaders In:
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 scale infinitely and never hallucinate.
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 Mission
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.
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.
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.
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 The moment context shifts or a document is out of date, the AI has no way to know - or care.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.
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.
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.
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.
Hallucinations eliminated at the architecture level.
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 that cannot contradict your governance policies, no matter the input.
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.
The Technology Chain
Why this is different
The Archisus platform is not a single product - it is a three-layer cognitive infrastructure that transforms raw enterprise data into governed, auditable intelligence.
The Constitution
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.
The Engine
RDF triple store persists all knowledge as semantic relationships. SPARQL queries traverse the graph at reasoning speed. SHACL constraint shapes enforce correctness before any output leaves the system - the layer that makes hallucination structurally impossible.
The Reach
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.
Together, these three layers form an enterprise-grade cognitive infrastructure that runs inside your security perimeter, on your cloud, with full data sovereignty.
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.
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.
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.
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.
Deep dives into our architecture, algorithmic approaches, and deployed solutions.
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Examining what is needed for current AI models to perform the job of a Data Engineer by leveraging Ontologies, SHACL rules, and Orchestration Grammar.
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We publish what we build. If your engineering problem doesn't have an article yet, let's talk about it.
Start a ConversationGeneric 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.
"Supplier ACME-12 may have compliance concerns. You should verify their certification status before proceeding with this order."
"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
Zero
Hallucinations
Structurally eliminated, not prompted away
47+
Logic gaps
Surfaced per audit, invisible before
100%
Traceable
Every decision tied to a source rule
We don't sell a licence and walk away. We start with a deep diagnostic, prove value fast, then scale across your organisation.
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.
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.
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.
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.
In a nuclear environment, "likely" is unacceptable. You need certainty.
Outcome: Faster regulatory reporting, safer procedure guidance, anomaly triage with quantified confidence bounds.
Predictive maintenance predicts failure. Archisus predicts consequences and compliant actions.
Outcome: Fewer unplanned shutdowns, cross-silo insight in weeks, every decision explainable end-to-end.
A smart grid is useless if it doesn't have a brain. Sensors everywhere - alerts understood nowhere.
Outcome: Faster restoration, fewer truck rolls, higher reliability - with auditable decisions and operator-ready explanations.
Your regulatory framework is a knowledge graph waiting to happen.
Outcome: Faster approvals, zero regulatory ambiguity, and a full audit trail on every public decision.
Your project is a set of interlocking constraints. Your AI should reason over all of them, simultaneously.
Outcome: Fewer rework cycles, compliance confidence before ground breaks, and no cross-silo blind spots.
Clinical pathways are logic. Formulary rules are constraints. Your AI should enforce both, not guess at them.
Outcome: Safer prescribing, faster clinical decisions, and a traceable rationale that satisfies auditors and clinicians alike.
Your sales data tells you what happened. Archisus tells you why - and what to do next.
Outcome: Reduced stockouts, higher margins, and decisions that merchandising teams can audit and trust.
Help us build the future of enterprise intelligence. We are looking for exceptional talent to join our mission.
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.
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.
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.
2-week engagement · Fixed scope · No ongoing commitment required
We will be in touch shortly.
Enterprise Knowledge Graph · Archisus AI