NeuAIs Documentation

services/: Apps that answer user/API requests (auth, compute, storage, billing, mesh).

• infra/: The setup that lets those apps run reliably (deploy configs, cloud/edge setup, monitoring).
• infra/workers/: Tiny edge apps that handle simple requests close to users.
• libs/sdks/: Language-specific clients so other apps can call our APIs easily.
• docs/: Guides and references so people know how to use and operate the system.
• apps/: User-facing frontends/tools.
• agents/: Small AI programs that automate tasks within the platform.

Example: imagine “ShopCo,” a big retailer rolling out an AI-powered storefront service for thousands of stores.

• services/: The APIs that power the product—auth for logins, compute to run recommendation jobs, storage for product images/files, billing to charge stores, mesh to keep services talking.
• infra/: The setup to run it all—docker/fly/cloudflare configs, monitoring, mesh wiring—so the services stay online and reachable.
• infra/workers/: Tiny edge endpoints that respond fast at store locations (e.g., serve “what’s in stock nearby” with low latency).
• libs/sdks/: Ready-made clients so partners’ apps can call ShopCo’s APIs without writing raw HTTP.
• apps/: Dashboards/mobile/UI where store managers see sales and configure promotions.
• agents/: Small AI bots that auto-tune recommendations, pricing, or inventory alerts.
• docs/: The how-to and reference so people know how to integrate and operate.

• Here’s how “ShopCo” could use what’s already in this repo:

• Login & roles: services/auth, services/iam, DB perms in services/database/migrations/001_auth_enhancements.sql (compute/storage/functions scopes).
• Product media & files: services/storage (S3-compatible) and file endpoints; SDKs point to /storage/….
• Compute for recs/automation: services/compute (server) for running jobs/functions; infra/workers/compute for low- latency edge handlers at stores.
• Network glue: services/mesh-network plus infra/workers/mesh-network to keep services discoverable across sites/ regions.
• Billing/charge stores: services/billing with compute/storage/functions pricing and Stripe hooks.
• Client integrations: libs/sdks/nodejs and libs/sdks/python (compute, storage, etc.) so partner apps call APIs without raw HTTP.
• Ops & deployment: infra/docker/docker-compose-full.yml to run the stack; infra/cloudflare, infra/fly.io, docs/ deployment/* for cloud/edge routes and tunnels.
• Frontdoor/API doc: docs/api/* (compute, frontend strategy) to describe the endpoints the UIs/SDKs use.
• Observability: infra/monitoring (Prometheus/Grafana/Loki) references for watching the services.

What they’d get from this stack (vs DIY):

• Ready-made services: auth/roles, storage, compute/functions, billing, mesh.
• Edge + server split handled: central compute service plus Cloudflare worker for low-latency paths.
• SDKs: Node/Python clients so partner apps integrate quickly.
• Deployment scaffolding: docker-compose, Cloudflare/Fly configs, mesh setup.
• Billing logic: resource pricing and Stripe hooks already in services/billing.

Why not DIY: they’d have to design/run auth, storage, compute APIs, edge routing, mesh, billing, SDKs, monitoring, and docs from scratch. This repo gives a head start, but some smoothing is needed to make it turnkey.

What else ShopCo would need to make it easy:

• Ready-made services: auth/roles, storage, compute/functions, billing, mesh.
• Edge + server split handled: central compute service plus Cloudflare worker for low-latency paths.
• SDKs: Node/Python clients so partner apps integrate quickly.
• Deployment scaffolding: docker-compose, Cloudflare/Fly configs, mesh setup.
• Billing logic: resource pricing and Stripe hooks already in services/billing.
• One front door: a consistent API gateway URL and routing rules (when to hit edge vs server).
• Single UI surface: a console page for compute/storage/functions; users shouldn’t see “service vs worker.”
• Default configs per environment: staging/prod manifests with sane ports/URLs/keys (docker-compose + worker deploy).
• Clear docs per audience: “How to launch” (ops), “How to call” (devs), “What it does” (exec). The audience map.
• Observability defaults: a simple way to spin up metrics/logs dashboards for the stack.
• SDK polish: one consistent Node client shape (currently two variants), plus “getting started” snippets per language.

This app to be intended as a way for business to automate all elements of what they do erfficiently via micro ai. Who essentially follow a ‘fig’ stler autocommand ruleset and each AI works within the boundary of a few automated and controlled areas. The AI offers intelligence, but they’re not too intelliget - thereby avoiding haulucination and resource sucking LLM, and uneccesary complication or risk.

• Business use micro AI agents to automate operations with minimal coding by leveraging prebuilt services and orchestrations. Users mainly configure policies, connect their data sources, and set safe operational boundaries. Key repo areas: services (prebuilt functions), agents (autonomous AI units), apps/dashboards (user interfaces), libs/sdks (integration tools), and docs/guides for onboarding.

Doc steps include: (1) “SAAS perpetually automatically running in 5 minutes” quickstart; (2) no-code/low-code flow explanations; (3) policy guardrails configuration guide. This will clarify usage with concrete examples and help users confidently engage with core capabilities.

Currently:

The promise is “micro-AI agents that automate business with minimal coding.”

• services (auth, storage, compute/functions, billing, mesh) + micro-AI agents that can run tasks for them. They don’t rebuild core cloud plumbing; they configure policies and plug in data.
• How minimal coding works: the agents do the heavy lifting. ShopCo’s team sets guardrails and triggers (e.g., “when inventory < X, reorder,” “if conversion drops, adjust promo”), not rewrite infrastructure.
  • Where it’s in this repo:
    • services/ gives the APIs the agents and UIs call (auth, compute/functions, storage, billing).
    • agents/ is the pattern for those “FIG-style” auto-commands—small, bounded behaviors.
    • apps/dashboard (and other apps) is where you’d expose a no/low-code UI for business users to configure flows.
    • infra/workers/* gives low-latency edge endpoints so agents can act fast without ShopCo hosting everything.
    • libs/sdks/ are for when they do need glue code; it should be light.

Still Needed:

• tool to connect their data (products, inventory, orders), set policies/guardrails, and choose which agents to enable. They shouldn’t be writing backend services; they’re configuring automations.
• Selling point vs DIY: faster time to value (plumbing and SDKs done), built-in edge + server path

A perfect setup would be:

• One manifest as source of truth: config/services.json listing every service/worker (name, kind, base URL, health path, routes exposed), env overlays for dev/stage/prod.
• Two enforced templates: a Go service template and a Cloudflare Worker template, both reading from the manifest for ports/paths, both exposing /health and common logging/metrics.
• Generators: scripts emit typed config for all UIs/backends (frontends import generated TS, backends import JSON/Go/Rust consts) so adding a service = edit manifest + run generate, no manual wiring.
• Single gateway: routes users to the right runtime (edge vs server) based on path/latency, hiding the distinction from users.
• One dashboard/control center: reads the manifest, shows health, and lets you connect data sources, enable agents, and apply policies; no hardcoded lists.
• Policy/templates + connectors: packaged data connectors and policy bundles stored in versioned JSON/YAML, selectable in the UI, executed by a policy/agent orchestrator service.
• Ops baked in: shared observability (logs/metrics/traces) and deployment configs derived from the manifest; zero per-service hand edits.

B2B Need

- Data hookups done for them: ship ready connectors (CSV/S3, Shopify, BigCommerce, Stripe,
ERP) and a guided wizard that ingests product/inventory/order feeds. Minimum: “drop a
CSV / connect store / paste API keys.”

• Policy templates: ship defaults like “auto-reorder when stock < X,” “raise promo when conversion dips,” “flag anomalies on refunds,” “block risky logins.” Let them tweak numbers, not write logic.

• Agent catalog with presets: each agent comes with a “turn on + choose data source + pick policy” flow. No code; just toggle and confirm scopes.

• Single control surface: one dashboard page that shows “data sources connected,” “agents enabled,” “guardrails,” with rollbacks. No “service vs worker” choices.

• Safe defaults + AI assist: recommend guardrails per vertical (“for apparel, reorder at 10 units”), and simulate changes before activating.

• Optional white-glove: if they want, we can import their feeds, map fields, and turn on a starter bundle of agents (e.g., stock protection, promo optimizer, fraud/abuse guard).