Three layers. One standard.
Most AI systems are powerful in isolation and unreliable at scale. We build the infrastructure beneath the model that changes that.
AiMe
AI that persists across sessions. Persistent identity, concern tracking, and proactive intelligence — the cognitive layer that turns a stateless model into a system that knows you.
Explore AiMe →Ethos
Behavioral evidence of what humans actually stand for — extracted from documented history across the full moral spectrum. Resistance-weighted, deterministic, and reproducible.
Explore Ethos →Verum
Cryptographic certification that AI outputs align with the behavioral value corpus. No LLM in the scoring stack. Deterministic. Signed. Independently verifiable.
Visit trust-forged.com →Everything we've built.
A complete cognitive infrastructure stack — from persistent memory to value alignment to open-source deployment.
AiMe
The operating layer that gives AI continuity. Persistent memory, concern tracking, proactive intelligence, and governed execution — built model-agnostic so the underlying LLM is interchangeable. The user relationship persists. The models are replaceable.
Ethos
Extracts behavioral evidence of human values from historical documents. Resistance-weighted, RIC-classified training data for value-aligned AI.
Verum
Scores AI outputs against the Ethos behavioral corpus. Cryptographically signed certificates. Model-agnostic. Deterministic — no LLM in the scoring stack.
Marshal
Autonomous infrastructure monitoring that detects developing problems before they become incidents — and acts with calibrated confidence. It never blinks.
ButterClaw
AiMe's governed cognitive architecture — truth separation, significance scoring, importance-weighted memory — running on OpenClaw's production-grade infrastructure. 87 messaging platforms. Multi-agent orchestration. Full plugin SDK. The brain of one. The reach of the other.
The company behind the stack
AI-nhancement LLC
A South Carolina-based technology startup founded by John Canady Jr. We focus on building durable AI infrastructure rather than single-session chatbot interfaces.
Our objective is to create systems where memory, execution control, and identity remain stable even as underlying AI models evolve. We develop orchestration runtimes that prioritize state persistence and architectural integrity.
Every design decision traces back to a single question: if you swapped the underlying model tomorrow, would the user's experience remain intact? If the answer is no, the architecture isn't done yet.
AI-nhancement LLC is fully self-funded and founder-led.
Founder
John is a self-taught systems builder with a history of designing low-level hardware and modern software extensions. He built AiMe's full cognitive stack — from the intent classification engine to the Living Portrait system — as a solo architect.
Prior to AI-nhancement LLC, he developed modern hardware extensions for classic Commodore computers under the commodore4ever name, including Wi-Fi modems and dual-display communication devices.
How we got here
AiMe v3 — Live as Primary System
v3 boots clean: all services, daemons, camera, voice, and embeddings operational. v2 is frozen. 44 pillar modules, 371 tests, 22 review rounds, 4 published papers. The architecture that ships.
Ethos & Verum — Dedicated Platform
Ethos and Verum launch at trust-forged.com as a standalone platform for value extraction and integrity certification, separate from the core AiMe stack.
Spine Swap Complete — 4 Papers Published
REQUEST loop removed from Cognitive Bridge v8.0.0: ~600 lines cut, 6 contaminated files deleted. Core invariant restated: "The model makes no decisions. The model produces language." Four academic papers written: RIC, Bond-Indexed Memory, Gravity-Weighted Significance, and Unified Architecture.
v3 Module Build Complete — 371 Tests
44 modules across 22 review rounds in two days: Task Model, Living Memory Advanced, Concurrent Tasks, Thought Formation, Experience-Enriched Memory, and Federation Architecture. "Specialists gather, governance decides, the language model speaks."
AiMe v3 — New Repository + SBA Spine
v3 established with dedicated root and canonical architecture. Phase 1: Self-Bounded Authority (SBA) Spine implemented — state builder, response synthesizer, authority engine, compliance validator. 31 tests. The governing layer that all output passes through.
ButterClaw Open-Sourced
First public GitHub presence under ai-nhancement. ButterClaw forks OpenClaw and ships truth separation, significance scoring, importance-weighted retrieval, and significance-aware compaction across 87 platforms.
Identity Continuity Phase 1A
Camera-based persistent identity verification. AiMe can now confirm who it is talking to across sessions — a prerequisite for true continuity of the Bond.
Multi-Thinker Unified Narration
Specialist cognition under one system-owned identity. Multiple reasoning thinkers operate independently while the system narrates as a single coherent voice — the user never sees the seams.
RIC Phases 2 & 3 Complete
Relational Integrity Coefficient expanded to a full five-subscale composite (G / C / T / H / P) with per-session Bond integrity drift tracking. 57 tests passing. Every conversational turn now scored before the user sees it.
Event Graph + Proactive Turn Initiation
Typed relational event graph with keyword-indexed traversal goes live (117 tests passing). AiMe begins initiating conversation autonomously — surfacing what matters without being asked.
Presence Awareness + SCAL
Return Recognition and Third-Party Arrival Detection go live with five absence tiers. SCAL (Semantic Conditional Awareness Layer) adds standing-interest pattern tracking with CompanionFilter safety gating.
RIC Phase 1 + Universal Values Registry
Relational Integrity Coefficient gates its first live turn. The Universal Values Registry Generation pipeline activates, using historical figure behavioral corpora to produce pre-labeled integrity training data across 15 human values.
Bond-Indexed Memory Formally Defined
"Memory is a relationship-indexed field. The index is not topic — it's Bond. The primary act is not recall. It is entering the Bond state. Memories surface as a consequence." The BFCS system class named. The Long Memory Plan complete.
Bond Object, Gravity Scoring, Latent Episodes
In a single day: Living Portrait created (six Bond dimensions), Concern Stack built on the Zeigarnik model, Gravity formula implemented, and Latent Episodes activated. The core relational memory architecture takes its final shape.
AiMe v2 — Git Repository Initialized
The formal v2 project begins. Foundational invariant committed on day one: "Memory is context, not output. The language model narrates with memory; it is never replaced by it."
Plugin Architecture — 15+ Plugins in One Day
A single session produces LanguageCortex (the narrator), ReactionCortex, Hippocampus (retrieval), TurnLedger, KnowledgeStore, TruthAdmitter, and eight more. The full plugin cascade is operational.
Computer Vision — Camera Hub + Thalamus
Vision system created in a late-night session starting at 1:47 AM: camera hub for visual input and Thalamus as the sensory relay plugin. AiMe can now see.
Services Architecture — Hybrid Retrieval
Multi-service retrieval backbone in place: Meilisearch for lexical search, dedicated embedding service for semantic search, and a retrieval fusion layer combining both. The architecture underlying all subsequent memory inventions.
Language Subcortex
New Year's Day, 12:53 AM. The expressive output layer of the three-part cognitive pipeline is built. The inventor was working.
Hippocampus — First Retrieval System
Named after the brain structure responsible for memory formation and retrieval. The first dedicated read-write retrieval system — predecessor to the hybrid Hippocampus that anchors the Bond architecture.
MACI Manifesto
System purpose formally articulated: "How does an intelligent system remain coherent, trustworthy, and continuous over time for one individual? This is not a system for scale, virality, or mass deployment. It is a system for belonging."
Christmas Day — Persistence Test
The inventor asks "Who is hazel?" nine times across separate sessions to verify that memory persists. It does. The system holds what it was told.
First Real Conversation Recorded
The evidence ledger captures its first real exchange: "Hello." "What is your name?" "I have 7 children…" Six days after the ledger was created, it holds a real human life.
Append-Only Evidence Ledger
The court transcript that is never rewritten. Every interaction appended permanently to an immutable ledger. Corrections adjust policy, not history. All subsequent inventions — Bond, Gravity, RIC — build on this foundation.
Cognitive Bridge v3.3
Three-part cognitive pipeline conceived and built: Memory Cortex (input/perception), Dual Cognitive Core (understanding/meaning), and Language Cortex (expression/response) unified into a self-reinforcing loop. Built at 2:02 AM.
Voice Integration + First System Prompt
TTS voice integration added December 1. The "AiMe Super Prompt" — the system's first formal behavioral contract — authored December 3. AiMe now speaks and has an articulated identity.
Core System Architecture Established
One day after first code: brain model with deterministic retrieval, provenance tracking, and gated learning ("child-like growth with safeguards"); full plugin cascade architecture; CLI entry point. The foundational cognitive structure — memory, reasoning, expression — is in place before the project has a name.
First Code: Persistent Memory with Embeddings
Four days after the development PC was assembled by hand in Saluda, South Carolina: the earliest surviving code timestamp. SQLite-backed persistent memory with FTS5 search and OpenAI embeddings. The file header reads "v4" — at least three prior iterations had already been built.
Hardware Origin
The development PC assembled by hand in the inventor's workshop in Saluda, South Carolina. The machine that would run the entire AiMe project, built before a single line of code was written.
Let's talk
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What I'm looking for
AI-nhancement benefits from partnerships that accelerate orchestration, tool expansion, and infrastructure scale.
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Cloud credits & startup programsCompute to scale orchestration, embedding models, and evaluation pipelines.
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API & platform partnershipsBest-in-class cognitive engines for specialized intent lanes with stable UX.
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Technical collaboratorsSystems engineering, distributed orchestration, and tool integration.