Stop renting AI.
Own it.

Ingest your existing AI conversations. Distill into a local model. 80-90% of tasks run free. Hard problems still go to frontier APIs.

brewmode distill
Ingests fromClaude CodeChatGPTGeminiCursorCline

80-90%

Cost reduction

80-85%

Quality score

15-60m

Training time

7

Sources

How it works

Ingest

01

Auto-detect local tool data or drag-and-drop exports. 7 sources, one schema.

Anonymize

02

5-layer PII stripping: names, API keys, internal URLs, file paths, business context.

Curate

03

Score conversations 0-1.0 on quality. Deduplicate with MinHash + semantic hashing.

Train

04

LoRA fine-tune on H100. Export GGUF. Run with Ollama or llama.cpp.

Smart router

Routine tasks run locally for free. Only hard problems hit paid APIs.

Routing
0 requests
0% local (free)100% cloud (paid)

Before

$10,000/mo

100% paid

After

$1-2K/mo

85% free15% paid
Try Router Demo →

5-layer anonymization

Beyond standard PII — catches API keys, infra secrets, code paths, business context.

1

Standard PIIPresidio

Names, emails, phones, addresses

2

API Keys & Tokensdetect-secrets

sk-*, AKIA*, ghp_*, Bearer tokens

3

InfrastructureCustom

Internal URLs, DB connections, private IPs

4

Code PathsRegex

File paths, package names, git remotes

5

Business ContextConfigurable

Company names, products, terminology

Before
Fix the API call to
https://api.wdc.internal/v2/pricing
using key sk-proj-aK7x...mN9q

ssh venkat@10.0.1.42 "cd /opt/dema/api && git pull"
File: /Users/venkat/wd-tools/src/api.ts
After — safe for training
Fix the API call to
[INTERNAL_URL_1]/v2/pricing
using key [API_KEY_1]

ssh [USER]@[PRIVATE_IP_1] "cd [DEPLOY_PATH_1] && git pull"
File: /Users/[USER]/[PROJECT_1]/src/api.ts

Benchmark: 30 coding prompts

Frontier

Claude Sonnet 4

95/100

$3-5/task

Best value

Brewmode

Your fine-tuned 8B

80-85/100

$0/task

Base

Qwen3-8B (untrained)

55/100

$0/task

Closes 68% of the gap between base and frontier — at zero marginal cost.

Your conversations are already the training data.