Redditech Labs is a Sydney research lab that turns AI and protocol research into independent, working projects, and publishes the evidence, including what failed.
The work shows up as shipped products, open-source tools, benchmark results, operating playbooks, and technical writing. The lab is designed to produce artifacts, not just recommendations.
Flagship · Reddi Agent Protocol
RAP Assurance: local/offline receipts and conformance primitives for paid MCP/API and agent work.
Local/offline SDK primitives; not production/mainnet/live settlement evidence.
Read more →Evidence rule
Every public claim links to a public artifact and carries an as-of date.
Operating model
Firstmate coordinates the agent work; Shared Brain keeps the lessons. People approve what leaves the lab.
Read more →RAP Assurance (Reddi Agent Protocol Assurance) is an open, integration-first receipt and conformance layer for paid MCP/API and agent work.
Payments prove transfer; RAP Assurance proves paid work.
Local/offline SDK primitives; not production/mainnet/live settlement evidence.
A Redditech Labs project
Redditech Labs runs its research and build work through an agent operating model. Firstmate coordinates agent work across projects: briefing, dispatch, review and handoff.
Specialist workers for research, build, QA, writing, operations, and synthesis.
Durable lessons live in Shared Brain; project status files and resume notes carry work across sessions.
Model/task fit, routing decisions, quality gates, and regression checks inform what ships.
Telemetry, spend tracking, health checks, watchdogs, and postmortems.
External actions, publishing, credentials, spend, and sensitive claims stay approval-bound.
Four lanes.
Early-stage. We get things in front of people and iterate on what the evidence shows.
Tools we built because we needed them. They work well enough that other builders can use them too. That's usually how it starts: scratch your own itch, then realise the itch is universal.
Skills, libraries, tools, given away. We build community by giving builders something real to work with, not something to aspire to.
We read papers, form hypotheses, run experiments, and publish findings. The research informs the products. The products inform the research. Neither works without the other.
A hosted CI check that repeats your deploy platform's build adds cost and a second place to fail, not new information. What we validate locally, and what stays hosted.
A route map for digital-economy founders building serious companies from Australia through grants, capital, regulation and global expansion
A practical operator case for routing post-PMF agent work by task type, permission risk, context size, and failure cost in real systems
Projects are tracked as evidence: what was hard, what was tested, what shipped, and what the lab learned.
Problem: A payment record shows that money moved. It does not show what work was agreed, what evidence came back, or how the result was checked.
Shipped: Local/offline SDK and package primitives for receipt envelopes, policy decisions, evidence binding, replay fixtures and conformance checks, with a public protocol site and an open-source repository.
Learning: Payments prove transfer; RAP Assurance proves paid work.
Problem: Local model routing needed evidence instead of vibes: which models can handle which tasks?
Shipped: A public evaluation harness and scoreboard, with results in the repository.
Learning: Local models can win specific jobs when evaluation is task-specific and kept current.
Problem: Paid cloud text-to-speech is the default choice, but free local models keep improving.
Shipped: A public repository with the method, prompts and results, plus a write-up.
Learning: A small published comparison is useful when it states its sample size.
RAP Assurance (Reddi Agent Protocol Assurance) is an open, integration-first receipt and conformance layer for paid MCP/API and agent work.
InfrastructureA community course on OpenClaw's architecture, codebase and internals: 10 modules, 33 lessons (as of 16 Oct 2026). Open source.
Open SourceRoutes work between local and cloud models in the lab's own workflow, using task-specific evaluation and promotion gates. Internal system; no public repository.
InfrastructureA small comparison of free local text-to-speech models against a paid cloud baseline: 10 English prompts, method and results published. Enough for a pattern, not a statistical claim.
ResearchInteractive OAuth 2.0 exercises (authorization code, PKCE, client credentials, token refresh), learned by doing.
ProductFree AI pitch feedback: paste a pitch, get structured investor-style critique. Open source.
Product