The AI spec layer — built from your conversations

You talk business.
We talk AI.

Most organizations are figuring out AI as they go. The gap between moving fast and building right is growing. Rikki turns your team's conversations into the specs your AI agents need — structured, governed, and traceable from day one.

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Business conversation in. AI-ready spec out.

Five lines of conversation becomes a structured, traceable, audit-ready build specification — before anyone opens a code editor.

Input — meeting transcript
Priya: The login flow needs MFA — we've had two incidents this quarter.

Raj: Agreed. TOTP or push? I'd lean TOTP — simpler to implement.

Priya: Works. Also lock the account after failed attempts — five tries?

Raj: Yes. Notify the user on their registered email when locked.

Priya: Perfect. That's the scope for this sprint.
Output — AI-ready build spec (excerpt)
## Functional Requirements

FR-001 Implement TOTP-based MFA on login 🟢
Source: Raj — "TOTP for now, simpler to implement"

FR-002 Lock account after 5 failed attempts 🟢
Source: Priya — "five tries"

FR-003 Session timeout after inactivity 🟡
Inferred — not stated; standard for auth flows

FR-004 Biometric fallback option 🔴
Assumption — not discussed; needs validation

## Security & Governance

SG-001 OWASP A07 — Auth Failures
MFA + lockout addresses brute-force attacks

## Testable Assertions

GIVEN 5 failed attempts
WHEN 6th attempt made
THEN account locked + email sent 🟢

## Gaps & Open Questions

GAP-001 Session timeout duration not discussed
Decide before build — affects UX and security posture
🟢 Explicitly stated 🟡 Reasonably inferred 🔴 Assumption — needs validation
This spec is ready to paste directly into Claude Code, Copilot, or Cursor.
Your AI agent reads the requirements, assertions, and gaps — and builds from them, not from guesswork.
Try it with your conversations →
From conversation to code
How Rikki turns business intent into AI-ready specifications
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💬
Step 1
You talk
A meeting, Slack thread, planning session, or voice note. Any business conversation where decisions are made.
→
⚡
Step 2
Rikki translates
Reads intent, separates explicit from inferred, scores confidence, applies governance, and surfaces what's missing.
→
📋
Step 3
Governed spec
Functional requirements, GIVEN/WHEN/THEN assertions, security governance, and full traceability — structured exactly how AI agents need it.
→
🤖
Step 4
AI builds sensibly
Copilot, Cursor, Claude Code — your AI assistants build from the spec. No vibe coding. No ungoverned output.
Every requirement
traces back to the exact words that created it
Every assertion
is testable before a single line of code is written
Every citation
is audit-ready from day one — not scrambled together later
Where Rikki listens
Meetings, Slack, email, planning sessions — wherever decisions happen
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🎙️

Meeting transcripts

Paste a transcript from Zoom, Teams, or any recording tool. Rikki reads who said what, identifies decisions and intent, and structures it into a governed spec.

"We need MFA on the login flow — two incidents this quarter."
💬

Slack & chat threads

Copy a Slack thread where a feature was discussed. Rikki extracts requirements from informal conversation — even if it was never meant to be a spec.

"Let's add a rate limit — maybe 5 attempts before lockout?"
📝

Planning sessions & docs

Paste notes from a sprint planning or whiteboard session. Rikki turns exploratory thinking into structured, traceable requirements.

"The dashboard needs real-time data — users complained about stale metrics."
📧

Emails & stakeholder feedback

Customer emails, exec direction, or informal feedback. Rikki structures the intent and flags what needs clarification before anyone builds.

"The client needs WCAG compliance before the contract can proceed."
🗣️

Voice notes & rough ideas

Early-stage thinking that hasn't been formalized. Rikki scores confidence on every interpretation — so you know what's solid and what needs follow-up.

"I think we might need versioning — not sure yet, worth discussing."
🔄

Corrections & iterations

When a build comes back wrong — paste the correction conversation. Rikki updates the spec and maintains the full history of why things changed.

"QA flagged three issues — here's what they found in testing."
What changes with Rikki
The organizational shift to AI — what it looks like before and after
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Today — without Rikki
With Rikki
60–80%
of meeting decisions never reach structured requirements — Standish Group
○Decisions stay in someone's head — context scattered across notes, messages, and memory
◆Every conversation captured and structured — AI-ready spec before the meeting ends
AI amplifies ambiguity
Vague prompts produce fast but ungoverned output — Gartner 2025
○AI agents get unstructured inputs and produce unpredictable output — ungoverned and untraceable
◆AI agents build from governed specs — sensibly and traceably, with human review at every gate
Day 1
traceability from every conversation Rikki processes
○Compliance reviews happen late — the audit trail is missing or invented after the fact
◆Governance baked in from the start — every decision traceable from conversation to code
42%
of institutional knowledge lost when a key person leaves — even more so in the AI era — Panopto 2019
○Context walks out the door — institutional knowledge disappears with every departure
◆Context stays with the org — searchable and structured, independent of any individual
Human judgment stays in the loop
○AI builds autonomously — no review points, no visibility into what was built or why
◆Intent Gate before build, Ship Gate before production — humans in control at every key decision
30–35%
SDLC productivity gain — only for orgs that redesign for AI, not those that bolt on tools
○AI tools added to an unchanged workflow — most of the productivity potential left unrealized
◆Rikki's Rikki Framework — Envision → Create → Deliver → Evolve — a development cycle redesigned for the AI era
Governance applied automatically: OWASP Top 10NIST AI RMFISO 42001WCAG 2.2EU AI ActSTRIDEISO 27001NIST CSF
Products

Start free. Grow when you're ready.

The Rikki Skill is free — no setup, no infrastructure. Works inside Claude, ChatGPT, or any LLM you already use. The Framework Guide and Platform add depth for teams scaling across the organization.

Free

Rikki Skill

$0

Paste a business conversation. Get a governed spec your AI agents can build from — in minutes.

+Works in Claude, ChatGPT, or any LLM
+Conversation → AI-ready build spec with full traceability
+Confidence scoring on every interpretation
+Governance and security applied automatically
Paid — for teams

Rikki Framework Guide

$49 one-time

The complete playbook for leading your organization through the AI transition — from business conversation to governed, shipped code.

+Complete Rikki methodology and AI transition playbook
+Industry templates and governance reference cards
+Team structure guidance for every AI maturity level
COMING
Enhanced

Rikki Platform

Soon

Every conversation, every spec, every line of code — aligned, traceable, and audit-ready across your entire organization.

+Enterprise connectors — Jira, Slack, GitHub, Linear
+Spec-to-code alignment tracking and drift detection
+Continuous governance monitoring in production
🧠
The longer you use Rikki, the more valuable it becomes.
Every spec, every correction, every outcome compounds into organizational memory — searchable by people and AI agents alike. Your conversations become your competitive advantage.
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