ASTRA CORTEX —:—:—PT/EN
Discovery → Delivery
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MULTI-AGENT PIPELINE · DISCOVERY → DELIVERY

The completeproduct cycle, orchestratedby agents.

ASTRA Cortex runs discovery, definition, design, build and delivery with specialized agents, keeping human decisions at every validation gate.

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◇ Orchestration

One core. Five fronts.

The ASTRA Cortex core coordinates the discovery, definition, design, build and delivery fronts. Each front brings its own specialized agents, with full context flowing from one to the next.

discoverydefinitiondesignbuilddelivery

◇ The problem

Speed without direction is just noise.

AI made writing code faster. The rest of the cycle, discovering, deciding, validating and shipping, is still broken in the same old places.
01

Discovery thrown away

Interviews, evidence and learnings die in documents nobody opens. Weeks later, the backlog becomes a contest of opinions.

02

Decisions with no trail

Six months on, nobody remembers why that feature exists, which hypothesis justified it, or what it was supposed to prove.

03

AI without judgment

Assistants generate code fast, but with no product context, no quality gates and nobody accountable for the decision.

HUMAN-IN-THE-LOOP · FULL TRACEABILITY · VERSIONED AGENTS

AI tools generate code.
ASTRA Cortex builds product: with memory, judgment and a human in command.

One direction across every front

From validated insight to a review-ready pull request: a single thread, auditable end to end.
0from insight to PR
0AI runs audited
0specialized agents
0average coverage of generated tests

◇ How it works

Five phases. Four gates. One thread.

i. Discovery Agents research the market, run interviews and organize evidence to map where the real pain is, before a single line of code. scoutscout-2user evidence · synthesized interviews · mapped problems Human validation gate
ii. Definition Evidence becomes a structured brief: critical problems, solutions prioritized by impact and feasibility, and acceptance criteria tied to each finding. scribestructured brief · impact × feasibility prioritization · acceptance criteria Human validation gate
iii. Design Flows and clickable prototypes are born aligned to the design system, ready to test with real users. atelierclickable flows · high-fidelity prototypes · UI tokens Human validation gate
iv. Build Reviewed, tested code, traceable back to the evidence that started it. Every PR arrives ready for your review. forgeforge-2sentinelreviewed code · generated tests · pull requests Human validation gate
v. Delivery The app goes live on your infrastructure, monitored and self-healing. Learnings flow back into discovery and the next cycle starts smarter. heraldpulsemonitored deploy · self-healing · continuous learning The cycle closes and starts again

◇ Platform

Built for teams that won't give up control.

Traceability

End-to-end traceability

Every deliverable points to the evidence that originated it: from hypothesis to pull request, auditable in both directions, at any time.

Evidence #142Hypothesis H-07PRD §3.2Prototype v4PR #891
Telemetry

Visual management

Product status doesn't live in a spreadsheet or a meeting: it lives on screen, live, with AI cost per feature.

Control

Human-in-the-loop by default

Validation gates between phases and risk-driven review: the routine flows, the critical waits for you.

GATE · DESIGN → BUILD
Architecture review awaiting approval from you.
ApproveComment
Governance

AI governance that acts

Guardrails per project policy, from warning to blocking, budget limits with hard caps and an audit trail of every agent decision.

Active guardrailsCost limitsFull audit
Security

Dependency chain under watch

Dependency inventory generated on every build and continuous vulnerability scanning. Found something critical? The delivery doesn't pass.

SBOM per buildVulnerability scanBlocking gate
Delivery

Deploy on your infrastructure

From a VM to the cloud, the app goes wherever you say, with self-healing: if a deploy degrades, the platform diagnoses, fixes and tries again.

Your infraSelf-healingHealth checks
Architecture

Versioned agents

Declarative, reproducible, auditable configuration.

# agent.config
agent:   "forge"
version: "2.4.1"
model:   "tier-1"
gates:   ["human"]
output:  "pull_request"
Integrations

Connects to your stack

Works in your git repository, on the provider you already use. And the spec travels with the team: export it to the AI editor of your choice.

GitHubGitLabBitbucketAzure DevOpsGitea
Enterprise

Ready for your organization

Full isolation per organization, single sign-on with your identity provider and data that never trains models.

SSO · SAML / OIDCIsolation per organizationLGPD
Memory

Context that isn't lost

Each phase inherits the full context of the previous ones. Each cycle starts smarter than the last.

◇ Who it's for

One pipeline. Three points of view.

Product

From evidence to decision

Discovery that doesn't die in a document: it becomes hypothesis, brief and clickable prototype, all linked.

  • Market research and interviews run by agents, with your approval item by item
  • Journeys, impact × feasibility prioritization and user stories ready for execution
  • Clickable prototypes aligned to the design system, before spending engineering
Engineering

PRs that arrive ready

Reviewed, tested code with full context, in your repository, in your workflow.

  • Every PR arrives with tests, review and the spec that originated it
  • Quality gates hold what isn't ready; self-healing deploy ships what is
  • Works on your git provider and takes the spec to the AI editor of your choice
Leadership

Control without micromanagement

Real-time view of what agents are doing, what they cost and where they need you.

  • AI cost visible per project and per feature, with budget and spending cap
  • A single queue of what needs a human decision; the rest flows on its own
  • Complete audit trail: every decision has an author, context and evidence
  • Visual management by default: the question “how's the project going?” stops existing

◇ Frequently asked questions

What everyone asks first.

No. Human validation gates exist between every phase and each pull request can require your approval. You choose the level of autonomy per project: from routine work that flows on its own to critical work that always waits for a human.

On your turf. Code lives in your git repository (GitHub, GitLab, Bitbucket, Azure DevOps or a self-hosted instance) and the app is deployed on the infrastructure you point to, from your own VM to the cloud.

Never. Your data stays isolated per organization, encrypted in transit and with secrets encrypted at rest, and it is not used to train any model. Guardrails block secret leakage by default and, according to project policy, personal data and other improper content.

Yes. ASTRA Cortex works on new products as well as existing codebases: agents read the repository, respect the defined architecture and evolve what's already there.

You see it and you cap it. Every project has an AI budget with a real-time meter, cost visible per feature and ceilings that stop execution before overrunning. No surprises at the end of the month.

Early access is open to product teams, with assisted onboarding included. Request access and our team will get in touch to set up the first project with you.

Multi-agent product pipeline

◇ Early access

Your next product starts today.

Limited early-access spots for product teams. Assisted onboarding included.

Request early access

No credit card · 15-minute setup

◇ About Webnuvem

Made in Brazil, for the world.

Webnuvem is an engineering studio from São Paulo obsessed with one question: what if the entire product cycle, from the first interview to deploy, could run on a single thread, with AI doing the heavy lifting and people deciding what matters?

ASTRA Cortex is our answer. Built in production, in our own day-to-day, before reaching yours.

CompanyWebnuvem
ProductASTRA Cortex
Based inSão Paulo, Brazil
StageEarly access
Contactcontato@webnuvem.com