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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Results for “llm cost per token”

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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LLMsOct 12, 202611 min read

LLM Batching Explained: Static vs Dynamic vs Continuous

LLM servers use three batching strategies to group requests. Static batching waits for all requests to finish. Dynamic batching stops waiting for a full group. Continuous batching frees slots immediately when requests end.

From Analytics Vidhya

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: support.

Archive (93)

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 “llm cost per token”

LLM Batching Explained: Static vs Dynamic vs Continuous

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