Private AI · Now in beta

AI that never sees
your data.

Pre-tuned domain LLMs for marketing, finance, legal, medical, and government. Deployed on hardware we let you audit. Ask for a quote — free composer is always free.

9.5×
Inference speedup
70%
DARE-TIES · GSM8K
4 live
Production products
Frankenstein composer: drag two base models, pick a recipe, get a hybrid LLM
Architecture built on production-grade open source
llama.cpp mergekit HuggingFace FastAPI Tailscale Stripe Supabase

Built for industries that
can't use ChatGPT.

Six verticals where compliance, privacy, or competitive risk make cloud LLM a no-go. We're the only AI option when "send it to OpenAI" isn't on the table.

Marketing teams

Ad performance, CRM, conversion logs your competitors mustn't see. Trained on your funnel.

Law firms

Privileged client docs, contracts, due-diligence files. Privilege never leaves your jurisdiction.

Hospitals & pharma

X-ray, CT, MRI, patient records under HIPAA / 個資法. On-prem deployment included.

Finance teams

GL entries, treasury, SOX-bound data. Reconciliation, variance analysis, month-end accruals.

Customer service

Ticket transcripts and known-defect logs that mustn't leak across customers via shared LLMs.

Government & defense

Classified docs, policy drafts, cross-agency comms. Foreign cloud AI is not an option.

Creative studios

Novel / manga / story brief → reproducible production pipeline. Engineering, not prompt gacha.

App developers

On-device iOS AI apps with zero API cost. Privacy-by-default mobile primitives.

Safety architecture

Bounded autonomy.
Brain gate blocks irreversible actions.

Parallel Claw runs 20 specialist lanes on your task. Auto-prepares the work. Pauses for human consequence. Blocks buy, sell, merge, publish, send before they happen.

This is the safety layer (MASL) under every Charenix product — 1,000-case evaluated, published on Zenodo (DOI 20071372), open-sourced at 23⭐ AFU Brain.

Parallel Claw: 20 specialist agents with Brain Gate safety, bounded autonomy

Four products live.
Three more in beta.

Every product is in production today. Open them in a new tab and try without signup. Paid tiers swap into dedicated hardware isolated from federation traffic.

You're not actually comparing us to Claude.

If using Claude or ChatGPT were an option for your data, you'd already be doing it. Here's what your alternatives look like when they aren't.

Capability
Charenix
OpenAI / Claude API
DIY mergekit + self-host
Data stays on your hardware
Yes — dedicated tenant
No — vendor servers
Yes — but you maintain it
Pre-tuned for your vertical
Yes — 6 verticals shipped
No — general purpose
DIY · weeks of setup
Downloadable model weights
Yes — GGUF on Pro+
Never
Yes — but you produced it
Predictable monthly billing
Flat fee, no per-token
Per-token; bill scales with usage
Free + GPU lease
Compliance-ready (HIPAA / SOX / 個資法)
Enterprise tier · on-prem option
Cloud DPA · still vendor-hosted
DIY · no auditor will sign
Maintained over time (security patches, base updates)
Monthly · part of subscription
Vendor updates
DIY · you forget, model rots
Reasoning quality on general tasks
Below Claude Opus / GPT-5
Industry leading
Same ceiling as us

We don't try to beat Claude on general intelligence. We're the answer when "use Claude" isn't on the table.

"

Big Cloud sells you the world's smartest intern. We sell you the only one who's allowed in your office.

Ho Yiing Chen (陳禾穎) Founder · Independent AI Researcher · 20 papers, May 2026

The infrastructure under every product is open.

Five tools we built for our own work, released so you can audit, fork, or replace any layer of our stack. 85+ collective GitHub stars and growing.

The founder thesis

AI agents need a
nervous system.

441 parameters across 12 published architectures form the substrate for long-lived LLM agent societies. OpenClaw, Hermes Claw research, Relational Cognitive Telemetry, LOBSTER-Bench, MASL, Alfred.

What you see in Frankenstein and Alfred is the surface. The substrate underneath is six months of measurement, twenty papers, and one person rebuilding LLM observability from scratch.

AI agents need a nervous system — Ho Yiing Chen (Norika Oda), Charenix Lobster Observatory
20

Papers on Zenodo · May 2026 alone

Every product decision is grounded in published research.

Cross-architecture LLM observation. Model merging failure modes. Multi-agent emergence. Safety layer evaluation. Verified by ORCID, archived on Zenodo, all code open. Not vibes — measurements.

See all 20 papers

Start with the free composer.
Plug in your data when you're ready.

No signup required to try Frankenstein. Drag two models, pick a recipe, chat with the result. 100 generations a day, forever free. Upgrade to private RAG when you want to bring your own data.

No card required for free tier · 7-day trial on paid tiers · Cancel anytime