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NVIRIA · RIVA

AI-native Operating System for trusted software development

RIVA turns AI coding speed into trusted engineering outcomes: an OS for how teams and AI plan, change, prove, and ship on enterprise codebases.

Govern Prove Ship

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The story

AI codes fast. Uncontrolled speed is the new risk.

The hype promised velocity. Teams got unbounded diffs, fragile changes, and token burn, while enterprise codebases stayed hard to understand, hard to verify, and harder to keep healthy.

Speed without a control plane breaks trust. Agents rewrite across modules; errors pass informal review; joins fail while units stay green. Retries burn tokens, and still leave no shared proof of what is safe to ship.

Enterprise codebases amplify the cost. Brownfield systems punish blind generation: hidden joins, drifting docs, no durable map. Model memory is not a system of record. Quality stays private: local tests or merge by impression.

RIVA is the next step. Governed work on the enterprise repository: map truth, pin a baseline, change under blast radius, verify in tiers, and ship with reusable evidence, so speed does not become uncontrolled debt.

Without governance

Uncontrolled AI Edits · Defect-Prone Joins · Merge by Impression · Token Burn on Retries · Quality Criteria Reinvented per Person

With RIVA

One Shared Baseline · Gated Acceptance · Unit, Integration, and Journey as the Common Bar · Evidence Reusable by Humans, Agents, and CI

Missions in the AI era

Where RIVA is pointed

North Star

Build the AI-native operating system for software development that turns AI coding speed into trusted engineering outcomes.

01

Operating System

Become the OS layer for AI-era software development on enterprise codebases. Replace one-off coding chats with a shared control plane the whole team runs.

02

Quality by Default

Make trusted engineering outcomes the default after every AI acceleration. Unit, Integration, and Journey keep quality on the standard path.

03

Human–AI Collaboration

Enable teams and AI to operate as one system with shared context and clear roles. Keep human judgment in the loop where risk and release decisions matter.

04

AI Speed & Infrastructure

Multiply coding throughput without uncontrolled edits or wasted token burn. Build AI infrastructure that keeps that speed reliable and reusable for the team.

Technology

Local-First Control Plane for AI Change

RIVA is built as layered product technology: workspace governance, multi-surface control, graph-aware workflows, and a structured quality bar grounded in source code.

01 · System of Record

Codebase as Truth

Analysis and verification start from the live repository. Docs inform; source decides. HEAD is characterized before large AI edits.

02 · Structure

Graph-Aware Scope

Structural maps and blast radius tell agents and humans what a change can touch, and what must stay green.

03 · Quality Bar

Unit · Integration · Journey

Three verification depths: isolated behavior, composition joins, and cross-layer paths, not line coverage theater.

04 · Control

Gated Agent Loops

Prepare → Agent → Gate → Advance. Progress requires met criteria. The model’s reply is never the definition of done.

05 · Surfaces

IDE · MCP · CLI / CI

One contract across editor, agent tools, and pipelines: the same prepare, verify, and lock semantics.

06 · Governance

RIVA Workspace

Team-scale quality: shared baseline, acceptance gates, and evidence packs for review and continuous integration.

Operating Sequence

Map & Baseline Scope Change Gated Agents Verify Tiers Evidence & Lock
Architecture

How the System Fits Together

A layered operating system: workspace governance on top, control surfaces, workflows, quality tiers, and an engine anchored in the codebase as System of Record.

System Overview

RIVA Workspace Shared Baseline, Gates, Evidence
IDE Operator Controls
Agent MCP Structured Tools
CLI / CI Pipeline Gates
Workflows Baseline · Quality · Change · Team
Unit Isolated Behavior
Integration Composition
Journey Cross-Layer Path
Engine Analyze · Handoff · Gate · Evidence
Codebase System of Record · Characterized HEAD
Layer 01

RIVA Workspace

The shared control plane for quality across the team. Establishes a single baseline, acceptance criteria, and evidence contract used by developers, AI agents, and CI.

Governance

Baseline Policy

Pins verified HEAD behavior as the reference for later change.

Acceptance Gates

Work advances only when criteria pass, not on model claims.

Evidence Contract

Standard provenance and regression packs for PRs and CI.

Layer 02

Control Surfaces

A consistent interface for humans, coding agents, and automation. The same prepare, verify, and lock semantics apply in the IDE, in agent sessions, and in CI.

Interfaces

IDE

Initialize, loops, impact, and next steps inside the editor.

Agent tools (MCP)

Context, handoffs, and verify actions for coding agents.

CLI and CI

Same gates and evidence artifacts in automated pipelines.

Layer 03

Workflows

End-to-end operating sequences for AI-assisted development on existing systems, from establishing trust in the codebase through change delivery and organizational enforcement.

Operations

Baseline Initialization

Map the repo, characterize behavior, lock a baseline before AI edits.

Quality Verification

Run Unit, Integration, and Journey as one quality bar.

Change Delivery

Blast-radius scope, gated handoffs, re-verify, evidence pack.

Team Enforcement

One definition of done for contributors, review, and CI.

Layer 04

Quality Tiers

A structured quality model derived from system structure, not line coverage alone. Each tier answers a distinct question about correctness under change.

Quality

Unit

Isolated function and symbol behavior after edits.

Integration

Composition checks across module joins at unit speed.

Journey

Cross-Layer Paths, with results in the evidence pack.

Layer 05

Engine

Local-first primitives that map the system, prepare agent work, enforce gates, and produce verifiable artifacts on enterprise repositories.

Platform

Structural Analysis

Symbol and dependency index for blast radius and context.

Handoff Orchestration

Scoped packages, agent sessions, completion tracking.

Gate Evaluation

Verify results before the workflow can advance.

Evidence and Lock

Provenance, regression output, optional baseline lock.

Layer 06

Codebase as System of Record

All analysis and verification are grounded in the live repository. Documentation informs; source code decides.

Source of Truth

Application Repositories

Live production code with modules, deps, and constraints.

Characterized HEAD

Pinned revision that later AI changes are measured against.

Get started

Comprehensive control plane. Simple install.

Bring workspace governance, gated agents, and a shared quality bar into the AI editor you already use. Install the extension, connect your repositories, and put shared gates and evidence around every change.

Cursor Claude Code Windsurf Copilot Gemini
01 · Install

Install the extension

Add RIVA to Cursor, Claude Code, Windsurf, Copilot, Gemini, or another supported surface. One contract across the editor, MCP, and CLI.

02 · Connect

Connect your workspace

Link application repositories to a RIVA workspace. Analysis stays local and grounded in your codebase as the system of record.

03 · Run

Run the flow

Baseline the system, scope the change, run gated agents, verify by tier, then lock evidence. You approve the gates; agents stay inside the blast radius.

Deep architecture. One extension to begin. Not a second editor, and not a cloud rewrite of your repository.

Request early access View architecture
Pricing

Choose how your team runs RIVA

Work alone on a personal control plane, collaborate in a shared team workspace, or run workflows tailored to your organization. Select the RIVA plan that matches how you deliver software.

Individual

A personal RIVA workspace across related application repositories — designed for a single operator.

$33 per month

  • One RIVA workspace
  • Up to three linked application repositories
  • Single-operator license
  • IDE, MCP, and CLI surfaces
  • Local-first control plane
Get Individual

Team

A shared RIVA workspace for your engineering team — people and coding agents operate against the same baseline.

$44 per seat / month

  • One shared RIVA workspace
  • Up to ten linked application repositories
  • Multi-seat collaboration (minimum three seats)
  • Shared baseline for people and agents
  • IDE, MCP, and CLI for the whole team
Get Team

Enterprise

RIVA configured for your organization — custom workflows, portfolio scope, and delivery under contract.

Custom priced on request

  • Everything included in Team
  • Custom workflows on demand
  • Multi-workspace and portfolio scope
  • Organization policy and continuous integration under contract
  • Named support with a service-level agreement
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FAQ

Why teams choose RIVA

How RIVA works with your AI editor, and what sets it apart.

What is RIVA?

RIVA is the AI-native operating system for software development: a local-first control plane that helps teams plan, change, prove, and ship on real codebases with reusable evidence.

Why choose RIVA?

Uncontrolled AI speed creates risk: unbounded diffs, fragile joins, and no shared definition of done. RIVA gives your team one baseline, gated agent loops, and a Unit · Integration · Journey quality bar.

How is RIVA different from Cursor or Copilot?

Coding agents generate and edit code. RIVA is the control plane around them: blast-radius scope, acceptance gates, structured verification, and evidence packs. Agents write. RIVA decides what is safe to advance.

Does RIVA work with Cursor and Claude Code?

Yes. Install RIVA on the AI editor you already use. Your agent keeps writing code; RIVA supplies prepare, gate, and advance across the editor, MCP, and CLI.

How is RIVA different from other AI coding products?

Most tools optimize autocomplete, chat, or unmanaged agent fleets. RIVA is built for governed change on brownfield systems: the live repository as system of record, graph-aware scope, and verification derived from system structure.

What does “codebase as system of record” mean?

Analysis and verification start from the live repository. Documentation informs; source decides. Model memory is never the definition of done.

How does RIVA turn AI speed into trusted outcomes?

Shared baseline and gates. Unit · Integration · Journey with evidence. Advance only after criteria pass—not on model claims.

Contact

Govern AI speed. Ship with proof.

Tell us whether Individual, Team, or Enterprise fits your team. We read every message and will get back to you.

Early access is by invitation. Share your team and codebase, and we will follow up with next steps.

We read every message and will get back to you.