Misikiri/Levelupp
Anyone can prototype with AI in an afternoon. Shipping to production is the wall — because the last mile needs domain judgment AI doesn't have. Levelupp turns your own knowledge into expert-validated guardrails that reach every build, inside Claude Code, Claude Desktop and any MCP-compatible tool. Self-seeded from what you already have. Built for any domain where being wrong is expensive.
Getting AI to build something is the easy part. Your agent can already reach your Confluence, specs, code and tickets — access was never the problem. The hard part is knowing which of it is authoritative, what's missing, and what needs an expert's sign-off before it shapes the build.
An AI agent will happily generate logic that reads well and quietly breaks a rule your domain runs on. The builder finds out weeks later — in review, or worse, in production.
Your AI can pull in everything — but it can't tell the authoritative rule from the outdated draft, or know what needs an expert's sign-off. The one validated answer still lives with a person who's now the bottleneck.
When someone asks "what guidance informed this?", a chat history is not an answer. You need provenance: which rule, certified by whom, applied where.
A prototype with realtime access to your human-validated domain expertise becomes more effective, efficient, accepted, scalable and accountable — and that is what makes it production-ready. Levelupp is the layer that sits between your AI product and the agents and models behind it, conducting and governing the build across that gap.
Certified domain knowledge is served to the build in realtime over MCP — your rules, standards and edge cases — and Validated AIDLC plans and routes each step from prototype toward production.
A workspace constitution gates risky actions before an agent ships them at machine speed; named experts certify, and every correction is captured and compounds.
The five things that make a build production-ready
Correct on your rules and edge cases, not just plausible — domain grounding lifts accuracy from ~50% to 80–95%.
Certified context cuts review rework — builds clear sign-off in days, not weeks of expert back-and-forth.
Backed by named experts and traceable provenance — answers users and stakeholders will trust.
One validated correction reaches every future build; the certified core compounds across teams and domains.
Every action governed, gated and audited, certified by named humans — safe to ship where being wrong is expensive.
Levelupp seeds itself from what you already have, puts every object through your experts' certification, and delivers only certified knowledge into the build — automatically, at the moment of prompting, governed end to end.
Levelupp lets your AI read what's already available across your company and run its own research, then pinpoints exactly what needs expert validation and what's missing — and opens the sessions to close those gaps. No blank page; it starts from your world.
Multiple experts contribute and multiple reviewers certify — conflicts surfaced and resolved. Uncertified knowledge is never served to builders. Certification is enforced at the platform level, not by convention.
Builders connect once via the Levelupp MCP. Certified knowledge becomes the validated requirements for what gets built, and Validated AIDLC governs the build to production-ready — gating risky steps, with object IDs and confidence on record.
You're a developer in Claude Code, or a PM building in Claude Desktop. Your AI is fast; your domain is unforgiving. Levelupp gives you a domain veteran at every prompt — without changing how you work.
No more digging through docs, chasing the right policy, or waiting on a review. The relevant rules, interpretations and edge cases arrive inside the prompt, at the moment of generation.
Every piece of context carries a named certifier, a date and a source. When someone asks "why did you build it this way?" — you have an answer with a name on it, not a chat history.
Thirty seconds to connect, then it's invisible until it matters. No portal to check, no document to search, nothing new to learn. If your prompt doesn't touch the domain, nothing changes at all.
The first time your enriched prompt flags an edge case you'd never heard of — a threshold your team set years ago, a reporting trigger, an override your company decided on — you'll understand the trade: you keep your speed, and you gain their twenty years.
You're the practitioner who knows how the rules are actually applied — the lead, the reviewer, the person every team comes to. Today that knowledge lives in your calendar. Levelupp puts it in the build — with your name on it.
One guided session replaces the same explanation given to every team, every quarter. The platform asks the questions; you talk. No writing, no prompt engineering, no new tools to learn.
Every knowledge object you certify carries your attribution — who said it, when, on what authority. Your judgment stops being anonymous review comments and becomes a durable, credited asset.
The usage ledger shows every build your knowledge shaped — which objects, which teams, how often. For the first time, you can see the leverage of what you know.
You sit down once. A guided conversation draws out the rule, the interpretation, the edge cases — the things you'd normally explain across a dozen meetings. Reviewers certify it. From then on, it arrives in every relevant build, automatically, without you in the room.
And this is where it goes: Domain Architects — public identity and income from the knowledge you've validated. The road ahead →
For the CTO, CPO or founder who pays for it: Levelupp is the validation layer that gets AI-built work from prototype to production — and keeps it defensible.
Anyone can paste a doc into a vector database. Levelupp is different: knowledge enters as unverified drafts and only becomes servable after your experts certify it — multiple contributors, multiple reviewers, conflicts resolved. The platform physically cannot deliver uncertified knowledge to a builder.
Only certified objects can ever reach a builder — enforced in the serving layer itself, not by policy.
Validated AIDLC — a dynamic, expert-validated development lifecycle, served live into every build.
Certified knowledge isn't just retrieved — it shapes how the work is done. Levelupp drafts a working lifecycle from your own codebase, your experts certify it, and it's served live: applied at the start of a build, gating risky steps on the path to production.
Each company gets an isolated workspace. Your internal policies and interpretations are never visible to other tenants, and builders are scoped to their workspace by their credentials. Every enrichment is logged — which builder, which prompt, which objects, at what confidence — your answer to "what guidance informed this?"
Levelupp MCP is the delivery component of the platform — a Model Context Protocol server that connects to Claude Code, Claude Desktop and any MCP-compatible client. One config entry, and every relevant prompt arrives enriched.
No portals to check, no docs to search, no workflow change. When a builder's prompt touches your domain, the AI calls Levelupp automatically and receives the certified context inline — clearly delimited and machine-parseable.
Retrieval gives you relevant text; Levelupp gives you certified knowledge. Every object served has been structured from your knowledge and signed off by your named reviewers, with the certification record attached. Uncertified drafts are filtered out at the platform level — they can never reach a builder.
No — that's the point. Your AI already reaches your docs, specs and code; Levelupp adds its own research on top, then works out what needs expert validation and what's missing, and opens sessions to close those gaps. Your experts certify. You're never staring at a blank page, and there's no knowledge base to build first.
A guided session is a conversation, typically about an hour — the platform asks the questions and structures the answers into knowledge objects. There's no writing, no prompt engineering, no tool to learn. Review and certification happen separately, by reviewers. Compare that with giving the same explanation in review meetings, indefinitely.
Three things today: leverage (one session ships in every relevant build, forever), attribution (every object carries their name, date and authority), and visibility (the usage ledger shows exactly which builds their knowledge shaped). On the roadmap: the Domain Architect program — public identity and income tied to usage of validated knowledge.
No. Workspaces are isolated. Your builders' credentials scope every call to your workspace, which layers privately on top of any shared baseline. Your overrides and additions are visible only to you.
It's domain-agnostic. Because Levelupp seeds from your own knowledge, it fits any field with rules, interpretations and expensive edge cases — software, operations, legal, healthcare, insurance and more. It's been proven first in regulated finance, where being wrong is unambiguously expensive.
Knowledge objects are version-controlled. Experts update or supersede objects, reviewers re-certify, and every builder is served the new version on their next prompt — no client updates, no redeploys.
Misikiri is the company behind Levelupp. Levelupp is the platform; Levelupp MCP is the component of the platform that delivers certified knowledge into builders' AI tools. Learn more at misikiri.com.
Levelupp is onboarding design partners — software teams building with AI who want their own validated knowledge inside every build. Bring your experts and your builders, and connect them in an afternoon.