Sciento model layer · Private scientific AI

Cortexa.
Your science. Your model.

A self-hosted family of biology and chemistry models, continuously tuned on your permission-scoped corpus and served inside your VPC, on-prem environment, or air-gapped network.

↳ Customer-isolated models↳ Eval-gated promotion↳ DPO / RLHF feedback loops
Cortexa logo
PrivateVPC, on-prem, air-gapped
Domain-tunedBiology + chemistry corpora
AlignedScientist feedback, DPO, RLHF
ControlledRegistry, evals, rollback
Why Cortexa

Frontier reasoning without sending your IP to a public API.

General-purpose models are trained on the public web, not your assays, sequences, protocols, and failure modes. External APIs also introduce privacy, cost, availability, and roadmap dependencies that regulated R&D teams cannot accept.

Cortexa gives each organization a private scientific model instance. It combines domain models, managed fine-tuning, embedding customization, alignment from real scientist feedback, and deployment controls in one model lifecycle.

Capabilities

A complete scientific model lifecycle.

01

Domain foundation models

Biology and chemistry models continually tuned on high-quality scientific corpora.

02

Managed fine-tuning

LoRA and full fine-tunes on permission-scoped customer data with isolated pipelines.

03

Scientist alignment

DPO and RLHF loops learn from approvals, corrections, and manuscript edits.

04

Task distillation

Compress high-value workflows into smaller specialist models for efficient hot paths.

05

Retrieval tuning

Fine-tuned embeddings improve search and grounding across private research corpora.

06

Model operations

Versioning, golden-dataset evals, gated promotion, observability, and rollback.

Model flywheel

Every scientific decision improves the system.

01Ground

Ingest the corpus

Curate public science and permission-scoped customer knowledge.

02Customize

Fine-tune privately

Adapt models and embeddings to the organization's science.

03Evaluate

Gate every version

Run golden datasets and safety policies before promotion.

04Learn

Capture feedback

Turn scientist corrections into the next alignment cycle.

Accelerated stack

Designed for sustained private training and inference.

DGX / HGXH100 / H200BlackwellNVIDIA NeMoNIMTritonTensorRTAI Enterprise
MVP pathContinually fine-tune an open-weight base model on Sciento's corpus, serve one private design-partner instance, and wire scientist feedback into a DPO loop before expanding to distillation and custom embeddings.

Own the model layer behind your science.

Deploy a private scientific model without surrendering control of your data or roadmap.