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Industry-Specific Models that already speak your domain

Healthcare, finance, manufacturing, retail, energy, legal, and logistics domain-trained AI — pre-trained on industry corpora, ready to fine-tune on your data.

Editor's pick

The industry-specific model most teams reach for first.

All categories
Editor's pick

Med-PaLM 2

Google Research·— params·Research API

Medical reasoning model surpassing USMLE pass-mark on board-style questions.

Spec sheet

Family
Google Research
Parameters
—
License
Research API
Status
Live
Best for
Models that already speak your domain
Sits in
Industry-Specific

Pricing and routing rank visible on InferenceBench. Variants and quantisations appear in the Yobibyte deploy console.

The rest of the lineup

5 more in Industry-Specific. All deployable in one click.

#
Model
Family
Params
License
Deploy
02
BioBERT

BERT pretrained on PubMed and PMC biomedical literature.

DMIS Lab
110M / 340M
Apache 2.0
03
FinBERT

Financial sentiment classifier trained on analyst reports and filings.

ProsusAI
110M
Apache 2.0
04
LegalBERT

Pretrained on EU and US legal corpora; strong on contract NLI tasks.

AUEB NLP
110M
CC-BY-SA 4.0
05
BloombergGPT

Finance-domain LLM trained on Bloomberg's 363B-token financial dataset.

Bloomberg
50B
Proprietary
06
ClinicalBERT

BERT pretrained on MIMIC-III clinical notes for EHR tasks.

EmilyAlsentzer
110M
MIT

Showing 6 of 50+. The full catalog (with quantisations, hardware variants, and per-region pricing) lives in the Yobibyte console.

Quick start

Five lines to your first industry-specific call.

Every model in this category is reachable from the same Yobitel SDK. Swap the model name; the rest of the call shape stays identical. Authenticated via your workspace key.

industry-specific-quickstart.py
PythonTypeScriptcURL
from yobitel import Inference

# Med-PaLM 2 — clinical QA with citations
client = Inference(model="google/med-palm-2")

answer = client.ask(
    question="First-line treatment for type 2 diabetes?",
    citations=True,
    audience="clinician",
)

print(answer.text)
for c in answer.citations:
    print(f"  → {c.source} ({c.year})")

Where teams ship this

Real industry-specific. In production.

Four use cases that customers run today. Pick a model from the lineup above, deploy on Yobibyte, plug it into the surrounding stack. Done.

  1. 01

    Clinical decision support and triage

  2. 02

    Financial risk scoring and compliance

  3. 03

    Legal contract review and discovery

  4. 04

    Scientific literature search and synthesis

Frameworks

Bring what your team already knows

TransformersvLLMMONAIBioMedLM stack

Yobitel handles the serving layer (GPU scheduling, KV cache, autoscaling, request batching) so your team focuses on the model and the product.

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Don't see what you need?

Bring your own model or fine-tune one of ours. Yobitel engineers can sit with your team and ship the right stack.