ITheons partners with global organizations to deploy intelligent systems that are grounded, transparent, and secure.
Explore our research →Engagements are covered by mutual non-disclosure. Named references are available to qualified buyers under NDA.
Ensuring large-scale models remain consistent with human values, organizational goals, and constitutional safety frameworks.
Infrastructure and fine-tuning for deploying robust large language models within secure, isolated enterprise environments.
Rigorous red-teaming and testing for bias, security vulnerabilities, and safety compliance across the full model lifecycle.
Developing safety protocols that don't just work for current models, but scale exponentially with the increase in compute and capability.
Proactive constraint modeling that prioritizes human agency and value alignment at every stage of the training pipeline.
Peering into the ‘black box’ to understand mechanistic foundations of model behavior before deployment.
“The most profound challenge of our age is not building intelligence, but ensuring that intelligence remains a faithful steward of human flourishing.”
Our safety architecture is built on the principle of defense-in-depth, combining automated red-teaming with rigorous human oversight.
Real-time monitoring against core safety axioms.
Automated systems testing systems for edge-case failures.
Strict isolation for testing unvetted model capabilities.
Each layer is independently versioned, independently auditable, and can be deployed inside your own network boundary. Nothing is a black box to the teams responsible for it.
How your applications reach the platform.
Every request is evaluated before and after inference.
Routing, retrieval, and tool execution under supervision.
Where the weights actually run.
The same platform, the same policy engine, and the same evaluation suite — delivered under whichever control model your regulator, your security team, or your board requires.
Multi-tenant, ITheons-operated
Single-tenant, your cloud account
On-premises, zero egress
| Foundation models | Claude Opus 4.8, Sonnet 5, Haiku 4.5 · GPT · Gemini · Llama · Mistral · customer-supplied weights |
|---|---|
| Fine-tuning | LoRA / QLoRA adapters, full-parameter SFT, DPO and constitutional RLAIF pipelines |
| Vector & retrieval | pgvector, Pinecone, Weaviate, Qdrant, Elasticsearch, Amazon S3 Vectors |
| Identity & access | SAML 2.0, OIDC, SCIM 2.0 · Okta, Microsoft Entra ID, Ping · attribute-based policy |
| Observability | OpenTelemetry traces, Datadog, Splunk, Grafana · raw event export to S3 / GCS |
| Runtime | Kubernetes 1.28+, containerd · Helm and Terraform modules · ARM and x86-64 |
| Support | 24/7/365 follow-the-sun · 15-minute P1 response · named solutions architect |
Certifications describe the floor. Every inference on the platform writes an immutable record of the policy that governed it, the model that served it, and the evaluation scores it passed — exportable for your own auditors.
Current reports, penetration test summaries, and subprocessor lists are available in the ITheons Trust Center. Request access →
A methodology for maintaining safety constraints when independent models interact in dynamic systems.
New benchmarks for evaluating reliability and hallucination rates in high-stakes economic modeling.
Defining the optimal balance between automated efficiency and manual ethical validation.
We are looking for researchers, engineers, and policy experts who believe that the challenge of safety is as exciting as the challenge of scale.
Interpretability, Alignment, Ethics
View Roles →Infrastructure, ML Ops, Security
View Roles →Governance, Compliance, Strategy
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