How do we stop employees pasting sensitive data into AI chats?

The extension and the desktop app check the text on the device and redact personal data and secrets before it is sent, under the policy your workspace sets.

How do we govern which AI models employees use?

Routing rules say which models may answer which requests - by data boundary, region, cost or team - and every request that broke a rule is in the audit trail.

Do people need training to use it?

No. The extension and the desktop app sit under the composer people already use and show the price and the pick; nothing changes in how they work.

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OpenSmartRoute

Blog

Results for “rejection sampling”

Daily notes on new models, LLM releases, agent frameworks and AI research, written from the sources we follow and delivered as a newsletter every day.

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All Models LLMs Agents Research AI

#ai 746 #agents 740 #news 653 #models 637 #llm 441 #research 331 #inference 309 #benchmark 123 #open-weights 116 #safety 98 #evaluation 83 #security 60 #automation 45 #open-source 37 #reasoning 37 #aws 34 #guide 34 #optimization 34

AISep 25, 20261 min read

Perplexity Trains Its Computer Agent on Real Mistakes With Hint-Guided Self-Distillation

Perplexity Research published a new post-training study. It trains a model inside Perplexity Computer on real user sessions, including failed ones. The method pairs rejection sampling fine-tuning with hint-guided self-distillation. In a ...

From MarkTechPost

LLMsSep 7, 20261 min read

MedProb: A lightweight framework for medical VQA answer prediction

MedProb is a probing framework that predicts multiple-choice Med-VQA answers from frozen vision-language model representations without free-text generation, outperforming prompting methods.

From arXiv cs.CL

Posts are drafted from public feeds by models OpenSmartRoute routes to - the same router, skill and metering customers use - and always link to the original source. Corrections: .

How this blog is made

Every post is a routed request.

Each feed entry becomes one request to OpenSmartRoute: the router picks a model with a cost-weighted objective, the editorial-writer skill is layered on the prompt, and the outcome trains the learners - the same pipeline available to every workspace. Open any post to see which target answered, its confidence, the alternatives and what the request cost. Run it yourself: register feeds in the operator console, map a small model under Providers, or call POST /api/v1/route with execute: true.

Photo: Yan Krukau

For the business

What it does for the people who use AI all day.

A quote under the composer
The price before you send
The browser extension shows the cost and the router's pick on the AI sites your teams already use.
The extension
A trace with every answer
Every decision explained
Which model answered, why it won, what it cost and what the alternatives were - kept for the retention period you set.
Open a trace
Checks on the device
Safe AI at every desk
Personal data and secrets are flagged and redacted on the computer, before a message leaves it.

Results for “rejection sampling”

Perplexity Trains Its Computer Agent on Real Mistakes With Hint-Guided Self-Distillation

MedProb: A lightweight framework for medical VQA answer prediction

Every post is a routed request.

What it does for the people who use AI all day.

The price before you send

Every decision explained

Safe AI at every desk