Aktiver — semantic AI platform Deterministic · traceable · behind your firewall
Platform

Bridge the gap between
data and decisions.

The only end-to-end platform that takes you from raw files to published knowledge graphs to reasoning agents — with a human in the loop at every step.

The pipeline

Any raw data in.
Decision advantage out.

Fig. 01 — End-to-end pipelineupdate with ease / live
Fig. 02 — Ontology alignmentRDF / OWL / OBO
Why Aktiver

Reasoning you can trust,
decisions you can trace.

Speed

Ontologies built in minutes. Unstructured data becomes a semantic layer while the meeting that requested it is still going.

Privacy

On-premises or hybrid deployment. Proprietary data stays behind your firewall — connected to public sources, never exposed to them.

Traceability

Every answer carries a clear evidence chain. Deterministic, non-stochastic reasoning — not black-box prediction.

Lower cost

Up to 50% GPU reduction. Structured knowledge means smaller models can outperform brute force.

End-to-end

Ontology management, graph publication, agent construction and inference — one platform, not four vendors.

Flexible deployment

Cloud-native architecture with no vendor lock-in. Run it where your risk profile says it should run.

The stack

Three components.
One continuous pipeline.

/ 01
AKTConnectData → Ontology
Converts PDFs, SQL, CSVs and JSON into structured ontologies. Subject-matter experts refine the result through a friendly interface, then export to OWL, Protégé or RDF — or connect straight into pre-built expert ontologies.
Auto-extractionSME refinementOWL / RDF export
/ 02
Pipeline IndexOntology → Agents
A drag-and-drop agent builder with access to 1.2M+ models. Every pipeline enforces semantic reasoning over your graph, so agents test fast and fail loud — ideal for research, intelligence and decision-making workflows.
1.2M+ modelsDrag & dropSemantic enforcement
/ 03
Agent CatalogAgents → Production
Curated, prebuilt agents for clinical, business and intelligence domains. Adapt them to your graph and deploy via Aktiver BOLT — modular, lightweight, minimal code.
ClinicalBusinessIntelligenceBOLT deploy
Versus the alternatives

Why not just RAG?

Pattern-matching → structure
RAG retrieves text. Aktiver retrieves meaning.

Structured semantic environments replace fuzzy similarity search. On complex multi-step interactions, that's worth 20–30% in reasoning accuracy.

Stochastic → deterministic
Same question, same answer, same evidence.

Non-stochastic reasoning means results are reproducible and every inference can be traced through the graph that produced it.

Specialists → everyone
No data science team required.

The people who hold the domain knowledge shape the ontology directly. Engineering effort drops to integration, not invention.

Monolith → modular
Agents measured in files, not repos.

Modular, lightweight agent design with minimal code — swap models, extend pipelines, keep the graph as your stable foundation.

See the pipeline run on your data.

Bring a folder of PDFs to the demo. Leave with a knowledge graph.

Book a demo