Presence Engine
Stateful Artificial Intelligence
Human-Centric AI Experience
Presence Engine™ is designed for continuity between people and machines.
It maintains context across interactions, adapts to individual rhythms, and operates with a privacy-first architecture.
Consistent, aligned, and built for long-term use.
Problem
AI answers fast, but understands nothing.
No memory. No tone. No awareness.
People need systems that can follow their thinking, retain context responsibly, and build understanding over time.
Learn moreApproach
Presence Engine™ maintains active context, not transcripts.
It tracks meaning, tone, pace, and intent so every interaction builds on the last. No resets. No starting over.
Built to evolve with you, not pass you.
Collaboration
Human-Centric AIX™ gives Presence Engine its adaptive layer. It interprets linguistic, and behavioral cues, then adjusts dynamically.
No profiling. No behavioral capture. No hidden inference.
Dignity is architectural here.
How it works
Presence Engine™ adapts to how you think.
It builds a continuity model: a live representation of tone,
pacing, semantic patterns, and contextual intent.
This allows persistent awareness without personal data retention.
Lightweight runtime
Learns tone, pacing, and context without collecting or retaining personal data.
Real-time adaptation
Updates continuously as you interact. No retraining. No session resets.
Privacy-first design
Operates locally or through encrypted endpoints. No profiling. No data resale. No background aggregation.
Always contextual
Retains patterns, never transcripts. Enough to stay aligned. Never enough to identify.
Deterministic safety
A real-time gate that enforces hard rules in 0.007ms. Not probabilistic. Not optional.
Identity that persists
No drift. No reset. Neve's personality, memory, and tone stay consistent across every interaction.
0 inference overhead
0.0006% of total turn cost. The substrate runs invisibly — fast enough that you never feel it.
Sovereignty by design
Seven violation patterns blocked at the architecture level. Dignity isn't a setting here.
PATENTS PENDING · BENCHMARKED
Foundation | Stateful AI
The stateful runtime layer. Presence Engine™ is built on the C³ Model (Context Capture, Coherence, Continuity), a host-native architecture that maintains awareness across interactions without storing personal data.
Overlay | Persistent Identity
The adaptive personality layer. Human-Centric AIX™ interprets linguistic, and behavioral cues in real time. It adjusts tone, pacing, and responds dynamically. Sovereignty is enforced deterministically,
not probabilistically.
95-100% gate accuracy across all test cases.
Research inspired by neuroscientist,
Dr. Michael Hogan, University of Galway.
"80,508 people told Anthropic what they want from AI. Continuity, dignity, and presence. That's what we built."
What 81,000 people want from AI ›
— Anthropic, March 2026
/ nɛv / COMING SOON
Neve
She's not your average sass-bot.
From the lab
Papers, technical updates, and applied research
Benchmarked at 0.007ms host-native latency
Structural overhead of 0.0006% of total inference cost
BENCHMARK RESULTS · Intel i7-10700K · RTX 2080 · 32GB RAM · Windows 11
LOM warm mean
0.007 ms
Full turn (Ollama)
844.5 ms
Structural overhead
0.0006%
Gate refusals
6 / 6
Cold path (run 0, 15.692ms) excluded. 50 warm runs of 50 total. 30 inference runs. Cross-run CV: 7.96%.
RESULTS | DOI: 10.5281/zenodo.19101284
Presence Engine: Deterministic Identity at 0.007ms Latency (0.0006% Overhead)
Presence Engine, a Logic-over-Model (LOM) substrate decoupling identity governance from probabilistic inference.
Benchmark results show 0.007ms warm-path mean latency (p99: 0.016ms) across 50 runs, representing 0.0006% of full-turn cost (844.5ms inference). Deterministic vetoes achieve 100% integrity (6/6) with randomized corrections, proving dynamic regrounding. Cross-run CV of 7.96% confirms stability.
DISSERTATION | DOI: 10.5281/zenodo.18636873
Neve: A Presence‑First, Sovereignty‑Preserving Stateful AI Architecture
Neve (/nɛv/) is a presence-first, sovereignty-preserving stateful AI architecture. It operationalizes concepts such as presence, dignity-first interaction, and cognitive integrity as concrete engineering constraints rather than abstract values. These constraints are implemented through persistent identity via C2C continuity tokens, OCEAN-based dispositional scaffolding, governed proactivity with explicit override and cooldown logic, and a risk-scaled ethics layer that shapes refusal and escalation behavior.
Read dissertation ›PAPER | DOI: 10.5281/zenodo.17755157
Stateful Reasoning Runtimes: Architectural Patterns for Identity Persistence Over Stateless LLM APIs
This paper introduces the architectural concept of stateful reasoning runtimes for LLM applications. Modern LLM APIs operate as fully stateless inference engines. Each call is independent and retains no memory of prior interactions. Current industry solutions externalize context using session replay, vector memory, and retrieval systems. These approaches reconstruct history, but they do not preserve identity continuity.
Read the paper ›