AI system for product teams. It helps you design a complete solution for each feature, and learns your decisions, code, rules and clarifications along the way.
Decisions
Rules
Code
Clarifications
The river: Your product’s
memory
One feature, nine parts, checked by your team
AI made building software fast. The slow part now is knowing your own product: why it works the way it does, which rule applies to which client, what was decided last time, which code is still used.
Why it works this way, which rule applies, which code is still used.
Old tickets, old documents, and a queue for the same experts.
They can read what’s written. The important things never were.
Step 1 of 3
A feature request, plus whatever already exists: notes, call transcripts, screenshots, documents, your code on GitHub. Rivora already knows what your team decided on earlier features.
Rivora drafts each part of the solution and asks the questions it can’t answer. The people who know answer, correct and approve. Each answer is kept as a decision, rule or clarification.
Approved work goes to Jira as stories ready to pick up, and to coding agents as a plan with the reasons attached. The next feature starts with everything your team has confirmed.
One question, answered once by the person who knows. Here is where that answer goes.
Illustrative example. The team and the policy are made up.
01
While drafting “Digital statements for members”, Rivora finds a gap the documents and code don’t answer. It asks which members are in scope at launch, and whether any, such as those on legacy policies, are left out.
02
The Head of Claims Operations answers once, in plain words: “Members on legacy NSW policies keep paper statements until June 2027.”
03
Kept as a decision, with where it applies and who confirmed it.
Decision · Active
Members on legacy NSW policies keep paper statements until June 2027.
Illustrative example
04
A person approves the stories before they go. The acceptance criteria carry the decision: “Members on legacy NSW policies remain on paper at launch.”
05
Claude Code receives the approved plan, with this decision attached.
06
“Statement-ready email notices” starts with this decision already in hand.
Answered once. Used in every feature it applies to.
PMs, engineers, designers, architects and experts each add what they know to the same feature, and everyone can see why it took its shape.
Requirements often say what should happen and leave the edge cases, business rules and expected behaviour unclear. Those gaps usually surface once building starts. Rivora raises them while the feature is designed, and the people who know answer. Engineers get approved stories in Jira and a plan their coding agent can follow, with the decisions and rules behind it.
Every AI tool on the team works from the same checked memory, so nobody re-explains the product in a new chat, and agents build from what is true today.
Products that have been around for years, are set up differently for different clients, follow strict rules, or depend on a few people who know how it all works.
The list keeps growing. Tell us which tool you’d like next.
“For ten years I have been the person who carries context from client to engineers. It gets tough as the product matures.”
Hence I built Rivora. I gave it the ability to learn context that matters, so teams can perform effectively.
I named it after a river: many streams of knowledge, joined into one, carrying products from idea to build.
Anurag Kapse
Founder, Rivora Connect
10 years in tech · Ex Product, Ex Agency · Sydney
You must be thinking
An AI system for product teams. It helps you design a complete solution for each feature, and learns your decisions, code, rules and clarifications along the way.
Product teams building on established software: products that have been around for years, are set up differently for different clients, follow strict rules, or depend on a few people who know how it all works.
A complete solution in up to nine parts, from the Executive Summary to the Delivery Backlog. Your team chooses which parts a feature needs, and checks every part before anyone builds on it.
From what your people say and confirm. When Rivora asks a question and someone answers, the answer can be kept as a decision, rule or clarification, with where it applies and who confirmed it. You can stop or replace any of them later. Nothing is learned silently.
Your team decides. Rivora drafts, asks what it can’t answer, and keeps what your people confirm.
Yes. Rivora reads your code through a GitHub App with read-only access.
We don’t use your content to train general-purpose AI models, and we will not knowingly permit our AI providers to use it for that. What Rivora learns stays in your workspace, as your product’s memory.
Rivora’s core hosting is on AWS in the Sydney region. Some providers we use for sign-in, AI processing, analytics and email may process limited data outside Australia. The Security page has the details.
Rivora is in early access, and we set up every team ourselves. Start with a Guided Pilot on one real feature, or book a free 30-minute session.
Plans start at A$680 a month plus GST on an annual plan, or A$800 a month on a monthly plan, priced by the features you design. The Guided Pilot is A$800 plus GST for four weeks.
Four weeks, with Anurag alongside your team. Or start with a free 30-minute conversation about your setup.
Guided Pilot: A$800 + GST, once. First we agree the feature and the people who should answer, then week one starts.
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