Catalyst · Digital Employees
CatalystAgent
The self-improving cognitive coding agent with persistent holographic memory.
Built on the Catalyst substrate — catalyst-brain HDC memory + catalyst-q quantum-grade solving — running its mind on Cloudflare's edge.
Investor Brief · 2026 · Strategic Innovations
The Problem
Coding agents are stateless amnesiacs.
- They forget every session. Context is rebuilt from prompts, never from lived experience.
- No cross-process learning. Knowledge dies when the process dies.
- Prompt-chain drift. Long agent loops hallucinate, repeat work, and degrade.
- AI slop avalanche. Stateless agents generate far more than they validate — shipping untraceable bugs.
Developers spend more time babysitting agents than the agents save them.
The Solution
A coding agent with a real memory substrate.
- Holographic brain memory — hyperdimensional neurons, not a prompt hack.
- Deterministic recall — the right context, selected by optimization, not stuffing.
- Edge-native — the brain lives on Cloudflare, milliseconds from your code.
- Model-agnostic cortex — routes across kimi-k2.7-code, glm-5.2, nemotron-3.
The core inversion
Everyone else lets the LLM both generate and decide. We let the LLM propose — and a deterministic Catalyst gate decides what's remembered, retrieved, and committed.
LLM proposes. Catalyst gates. Slop dies at the door.
How It Works
A closed-loop cognitive engine.
- HDC neurons encode tasks, errors, fixes & context as bit-exact hypervectors — distributed, noise-robust, content-addressable.
- Hebbian synapses strengthen on co-fire and decay when idle — the more an insight is used, the faster it recalls.
- CHAM QUBO context selection solves a combinatorial optimization for the minimal coherent context window under a token budget.
- Coherence gate scores novelty, confidence, saturation & evidence — low-coherence writes are blocked, not merged.
- Causal adaptation — an error followed by a fix becomes a linked memory pair; the fix returns automatically when the error recurs.
Why We Win
Memory is the architecture — not a feature.
| Capability | CatalystAgent | Claude Code / Hermes / OpenClaw |
|---|
| Cross-session recall | ✓ Native, HDC-backed | None or RAG bolt-on |
| Context selection | ✓ QUBO-optimal, minimal | Prompt expansion / heuristics |
| Output gating | ✓ Deterministic coherence gate | Stochastic sampling only |
| Error→fix learning | ✓ Persistent causal trace | Ephemeral logs |
| Token cost over time | ✓ Bounded by memory bundle | Grows with conversation |
| Deployment | ✓ Edge-native (Cloudflare) | Cloud-locked or local-only |
We win because we learn. They prompt.
Live Proof — Not a Slide, Shipped Infrastructure
Already deployed. Already remembering.
5/5
memory-on recall (live bench)
100%
bit-exact HDC bind/unbind
O(1)
constant-footprint memory
Edge
Cloudflare Workers + DO
- Cross-process recall: a fact stored in one terminal session is recalled in a freshly-launched one.
- Tamper-evident: every turn, tool call & memory decision is written to a hash-chained
.rain ledger that verifies.
- Self-authored: this deck's source was written by the agent itself, via its own
write_file tool.
The Moat — The Substrate, Not the Model
Built on Catalyst-Q's proven substrate.
- catalyst-brain — bit-exact HDC memory: reproducible, portable, auditable — not embedding black boxes.
- catalyst-q — a bounded-width virtual quantum substrate powering optimization & certificate-backed solving.
- Model churn survivable — swap the LLM, keep the brain.
Catalyst-Q · Public Benchmarks (Metriq PR #461)
Mirror Circuits (to width 64)1.0 exact
QML Kernel (10–50 qubits)1.0 accuracy
Linear Ramp QAOA0.7735 ratio
EPLG (100-qubit chain)5.97e-11
Competitors can add memory. They cannot copy a substrate built from first principles — and validated on the Unitary Foundation's public record.
Market
The coding-agent market is being won by tools with no memory.
- Claude Code — strong model, stateless session context.
- Hermes / Codex-style — impressive generation, no persistent causal learning.
- OpenClaw / open stacks — flexible, but every team rebuilds memory from scratch.
The wedge
A production-grade coding agent teams trust — because it remembers, learns, and gates itself.
Beachhead: engineering teams on Cloudflare / edge-native stacks.
Expansion: CI/CD, observability, automated remediation, enterprise knowledge-preservation.
The Ask
Turn the shipped prototype into the default cognitive shell for edge-first engineering.
Raising a seed round
40%
Engineering — catalyst-brain performance, QUBO scaling, memory security.
25%
Product — CLI UX, IDE integrations, memory-inspection tooling.
20%
Design partners — onboarding 5 teams with 50+ developers each.
15%
Operations — legal, infra, community & growth.
The next generation of coding agents will be defined by memory, not model size. Join us.
Contact
Let's build the agent that remembers.
Travis Crew · Strategic Innovations
sales@strategic-innovations.ai
pip install catalyst-brain · catalystagent-harness (open source)