TequilaEyeQ: Your Private Sovereign AI

Empower your organization with a private large language model that speaks your industry's language, safeguards your data, and continuously learns from both your internal systems and the global external sources, without leaking corporate data, ideas,challenges, and ip to external models.

 

 

 

TequilaEyeQ In Action

Income & Expenditure
Sales & Marketing Data
Proprietary Workflows
Competitor Analysis
Strategy & Performance
Product Roadmaps & IP
• PRIVATE INSTANCE • ZERO OUTBOUND TRAINING • LOCKBOX SECURITY • PRIVATE INSTANCE • ZERO OUTBOUND TRAINING
TequilaeyeQ
LLM CORE
Revenue Enhancement Strategies
Cost Containment
Investment Opportunities
Optimised Workflows
Competitor Analysis
Terminal Node — Sovereign Network Active
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TequilaeyeQ Protected Session Initiated. Base models safely isolated. Fed by your organizational assets on the left. Outbound particles will display synchronous text updates.

Unmatched Intelligence, Zero Compromise

Intelligence Stream How TequilaEyeQ Utilises It Core Benefit
Business Systems Connects to your internal data feeds with automated PII redaction and synthesis. A coherent and complete view of your organisations performance; complete data sovereignty and strict privacy compliance.
Proprietary Documents Scans and digests your company's files, manuals, and internal communications. Organisation focussed, industry-specific AI assistance.
External Sources & LLMs Analyzes competitor moves, exchange, interest rates, industry news governmental & tax policies, academic research Proactive, outward-looking strategic intelligence & Insights.

Frequently Asked Questions

So what exactly is a private sovereign llm?

There is a perception, and  evidence that proprietary IP is being  accessed and used for purposes for which it was never intended, and this is a concern shared by the European Union. Our LLMs can either run on your own infrastructure or on our private servers located in a tier one data centre located in Malta.

So how is it priced?

 The service is priced based on tokens, each data source is priced based on the number of data items it delivers, how complex it is to consume data from that source (api endpoint, csv, soap, email), how often you wish to update that data, and how long you wish to retain the data. You pay a fixed price per month, and then you buy a token plan. The plan gives you tokens to consume when accessing the llm; the more complex the prompt (query) the more tokens it will consume. If you run out of tokens you can buy more, these additional tokens will roll over for one month, so that if you don't consume them this month, they will be avalable for consumption the following month.

Does Tequila AI have access to your Data

That decision is entirely up to you, and the agreements you have with the data originators. Data is encrypted prior to the transit and ingestion phase, and the llm server does not  keep copies of the raw data. It does however keep the raw data meta data (origin, date), such that an authorised user can ask for the provenance of a response, purely so that a response to a prompts veracity can be checked). 

Is the LLM backed up?

Backups of the LLM are controlled by the tenant. All backups should be encrypted with the keys held by the tenant. We recommend that backups are stored on immutably storage (i.e. storage that cannot be changed once written to). Tequila AI can setup the backup to the tenants requirements if required.

Can your LLM be run on 3rd party cloud servers

No, Tequila AI doesnt support that. Primarily out of an abundance of caution for the security of our IP and our clients.

How long are your contracts

Contracts are typically for 3 years. That allows us to commerically lease the server.

Are LLM servers shared?

No, one tenant per server. 

Can the LLM be run on a server owned by my organisation.

Yes, but it must be dedicated to the LLM and it must be provided by Tequila AI.

does the LLM require a highly spec'd server?

That very much depends on the size of the LLM. A SME sized LLM can typically be run on a server the size of a shoe box. Large LLMs require higher spec'd servers which may have special power and cooling requirements which may not be served by a typical data centre.