Virtual analyst teams that replace entire research workflows—with measurable ROI.
Autonomous inference systems running 24/7 research pipelines across financial, legal, and scientific domains. Powered by SONA—Adaptive Vector Injection without weight modification.
SONA/AVIR writes episodic memory directly into LLM activations at inference time. No fine-tuning. No data leaks. No weight modification. Your AI gets smarter with every interaction — invisibly.
SONA/AVIR writes episodic memory directly into LLM activations at inference time. No fine-tuning, no data leaks, no weight modification. Your AI adapts with every interaction—invisibly.
Three temporal dimensions — Past (episodic memory), Present (contextual embeddings), and Future (policy vectors) — give agents a causal understanding of time, not just similarity.
All vectors live in hyperbolic Poincaré space with Lorentzian metric. This yields 1.585 bits per trit of information density — agents retrieve what is semantically reachable, not merely similar.
Elastic Weight Consolidation++ runs after each episode, protecting critical synapses while absorbing new patterns. Episodic memory consolidates to semantic memory without catastrophic forgetting.
Injected vectors exist only in activation space during inference. They cannot be extracted by probing model weights post-inference — the mechanism is invisible to model extraction attacks.
Causal Neuro Circuitry
Most AI companies sell acceleration. We sell replacement of entire workflows - with measurable ROI, not vibes. Virtual analyst teams that run 24/7 research pipelines across financial, legal, and scientific domains.
Modular agentic pipelines - each team member is a purpose-built reasoning chain with tool access, memory, and accountability. Derived from ruvector's operational vector database with 256-dimensional embeddings and cosine similarity.
Causal memory architecture grounded in relativistic geometry. Agents retrieve only what is semantically reachable, not everything that is similar. Polymathic weighting scores cross-domain relevance so agents surface unexpected connections.
Iterative transformer architectures that trade parameters for compute loops, getting more out of smaller models. Challenging scaling laws by injecting iterative reasoning into inference rather than adding parameters.
Every output is auditable. AI proposes, domain experts dispose. No black-box decisions reaching production. Deliberately guided inference with structured reasoning and verification gates.
Three temporal dimensions — Past (episodic memory), Present (contextual embeddings), and Future (policy vectors) — give agents a causal understanding of time, not just similarity.
All vectors live in hyperbolic Poincaré space with Lorentzian metric. This yields 1.585 bits per trit of information density — agents retrieve what is semantically reachable, not merely similar.
Elastic Weight Consolidation++ runs after each episode, protecting critical synapses while absorbing new patterns. Episodic memory consolidates to semantic memory without catastrophic forgetting.
Injected vectors exist only in activation space during inference. They cannot be extracted by probing model weights post-inference — the mechanism is invisible to model extraction attacks.
Proof
Human-supervised artificial intelligence across specialized domains.
Decentralized Finance Intelligence
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AI-Augmented Legal Research
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Scholarly Research Acceleration
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Intelligence Through Clarity
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Post-Quantum Private Auditable Ledger
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AI-Powered Privacy Research
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Ambition
Active research initiatives applying multi-agent intelligence to humanity's hardest problems.
Translating Human Intent into AI Action
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Healthcare Intelligence Without Borders
A healthcare intelligence system where rural health workers describe symptoms in plain language, and the swarm matches c…
Multi-Agent Scientific Discovery
A multi-agent swarm that coordinates literature review and hypothesis generation across multiple agents working in paral…
Real-Time Disaster Response Coordination
During natural disasters, a swarm coordinates information across all affected regions simultaneously - news, government,…
Our Purpose
Human intelligence, amplified for all. We believe the most transformative applications of AI serve those with the least access to expertise. Our developmental projects target underserved populations, accelerate scientific discovery, and make knowledge genuinely accessible regardless of wealth or geography.
Book a free consultation to discover how Aigentic can replace entire research workflows with measurable ROI.
Or email us: marketing@aigentic.net