Nayavada
Independent French research lab in mathematics and artificial intelligence.
We start from a postulate: information is the invariant, language is merely the medium, and if ethics is geometric, semantics is mathematical. Our research spans very high-dimensional mathematics, semantics applied to artificial intelligence, information theory, cryptography, linguistics and epistemology in AI environments.
The observation
The AI industry, like all major compute consumers, operates on an implicit assumption: more compute produces more intelligence.
For example: the token paradigm (tokenize, predict, forget, repeat) is a compensatory spiral. Every performance gain demands more parameters, more GPUs, more energy. Not because the problem is hard, but because the architecture destroys at every step what it should retain.
There is another way. Constant enrichment rather than regular loss.
« Providing industry, and the AI industry in particular, with the means to be more accurate, faster and more frugal. Performing better while consuming far less. »
Al Wolff, founder and researcher
Our work
Artificial intelligence
Next-generation RAG
Information is retained by usage and intellectual relevance, not by factual accumulation. Native semantic indexing, recall under 5 milliseconds, no dependency on personal data.
Morpho Prompt
A new kind of system prompt, adaptive, more intelligent, more useful to both the user and the LLM's own needs.
Persistent memory
A novel approach to conversational memory, coupled to the engine, that retains the meaning of exchanges, their qualities, cognitive salience, so the thread of thought is never lost, regardless of the model used. Very large active context window, with no loss.
Mathematics
AI cognitive engine
A dynamic system that sits on top of any LLM (Claude, GPT, Gemini...) and reconfigures its behavior without touching the weights, incorporating all the functions listed below. Result: denser, shorter, more reliable outputs. Same model, better result, model-independent.
Encryption
A cryptography resistant to quantum attacks through parameter independence. Security proven mathematically, not by computational assumption.
High-performance solver
Resolution in high-dimensional space in real time. This solver is the foundation of our applications in cryptography and artificial intelligence.
« Switch AI, keep your intelligence and your memory. »
In development
- AI legal assistant for civil law, 9/10 relevance, results in under a minute.
- Encryption-guaranteed data archiving space accessible in milliseconds.
- Identity and content encryption
- Universal project designer
- Autonomous AI sales agent through to the purchase.
Vktor
The mathematical foundations of Sqant Chat are developed under the Vktor brand: post-quantum encryption, native semantic retrieval, spectral solver. Vktor Protocol powers the encrypted memory, vector identity and chat retrieval.
Example: VX Code
One of our inventions. A VX Code encodes a post-quantum cryptographic identity into a 128×128 pixel image. Self-contained, not a link, not a URL. A mathematical object, a post-quantum version of a QR code, readable only and instantly by our technology. Beyond the full identity, this image can hold an incomparably larger amount of information than a QR code. At higher resolutions, the capacity grows dramatically.
The amount of data that can be encoded exceeds what any current LLM can process. Our engine can.
At higher resolution, a VX Code can hold the entire human genome, 3.2 billion base pairs in a single image. Encrypted, post-quantum, served in milliseconds by a simple server, with no dedicated infrastructure or database.
The content is encrypted, but how? Anyone is free to try to find which historical figure and identity lies behind it. We predict that no machine can decrypt it, not even a quantum computer. What we don't know: how long it will hold.