AI collaboration layer for your apps

One AI hub powering many apps — with clear cost and clean control.

BrainBus is a cutting-edge web app that lets your products share a single, well-governed AI layer. It was developed by Venturelogix to route model calls, track usage, and keep AI infrastructure sane as you scale.

Under the hood, BrainBus uses its own AI router to pick the best AI model for each request — balancing raw model cost against “expert” quality — so you get strong answers without babysitting vendors and price sheets.

See what BrainBus does View pay-per-use pricing

Designed for

Modern SaaS & agents

Optimized for

Cost, speed & model fit

Backed by

Venturelogix studio

At a glance

What BrainBus gives your team

  • • A single API endpoint for all your apps to call.
  • • Per-app API keys and usage tracking for clean billing.
  • • An AI router that automatically chooses the best model for each request.
  • • A straightforward story your team, buyers, and investors can trust.

Built by Venturelogix

BrainBus is part of the Venturelogix product stack — the same studio that prototypes, pressure-tests, and spins out AI-first web apps. It exists because managing AI across multiple products shouldn’t be a pile of one-off scripts and wishful thinking.

What BrainBus does for your stack

At its core, BrainBus is an AI collaboration and routing layer. Instead of each app integrating directly with every model provider, they all talk to BrainBus.

  • One integration, many models. Your apps call BrainBus; BrainBus speaks to providers like OpenAI, Anthropic, Mistral, and others via a single upstream connection. Swap or add models without redeploying every product.
  • Per-app keys and clean separation. Each web app, micro-service, or agent gets its own API key. That means per-app usage, per-app limits, and a clean picture of what’s actually driving spend.
  • Usage & billing handled by design. BrainBus tracks calls, applies your pay-per-use rules, and exposes clear usage data. It’s built to support pay-per-call APIs, SaaS bundles, and reseller-style flows where you control your own markup.
  • An AI “dispatcher” that picks the right model. BrainBus uses AI to classify requests and send them to fast, cheap models when it can — and higher-end “expert” models when it should — so your apps feel smart without you hand-tuning every endpoint.

Example: your app calling BrainBus

POST https://api.brainbus.net/ai

{
  "api_key": "app_xxx_key",
  "model": "auto",
  "messages": [
    { "role": "user", "content": "Draft a welcome email for new users" }
  ]
}

BrainBus authenticates the key, uses its AI router to select the right model profile (fast, balanced, or deep), forwards the request upstream, and returns the response to your app — along with usage info you can use for analytics or billing.

How BrainBus works under the hood

BrainBus was built to be boring in the right ways: predictable, inspectable, and easy to reason about. Under the hood it’s a routing and metering service with a very simple mental model.

  1. 1. Your app sends a request.
    You send a JSON request with your api_key, a model (or "auto"), and a set of chat-style messages.
  2. 2. BrainBus authenticates and classifies.
    BrainBus looks up the app, its billing mode, and how many calls it has made in the current period. It also uses AI to classify the request (short prompt, long-form, deep reasoning, code, etc.).
  3. 3. The right model path is selected.
    Based on that classification, BrainBus chooses a routing profile (fast, balanced, deep, long-form) and sends the call to the best-fit model for cost and quality — without you wiring every model directly.
  4. 4. The answer is returned and usage is logged.
    The response goes back to your app; BrainBus logs a usage record with model, estimated call cost, and metadata you can use for your own pricing and reports.

Why teams like it

Easier to integrate, easier to explain

Your engineers get one stable interface. Your non-technical stakeholders get one clear diagram. Everyone knows where AI lives in the architecture.

Control over cost without handcuffing innovation

Routing profiles and usage metrics live in BrainBus, not spread across a half-dozen dashboards. You can experiment with new AI features without losing sight of what they cost.

Future-proofed vendor strategy

Providers change, prices move, models evolve. BrainBus keeps your apps steady while you adjust the routing and model mix one level below them.

Simple, pay-per-use pricing

Instead of fixed “plans” and hard limits, BrainBus runs on a pay-per-use model. You pay only when your apps actually make AI calls, which makes it easy to layer BrainBus into existing SaaS pricing and keep your margins healthy.

Every call includes: routing logic, model selection, metering, and usage logging — you add your own markup on top.

Pay as you go

From ~$0.01 per AI call

Light, fast requests route to cheaper models; heavier or “expert” work routes to higher-end models. Your average cost per call stays low while quality stays high.

  • • No monthly minimums baked in by default.
  • • You can bundle BrainBus into your own SaaS plans.
  • • You keep the difference between your price and BrainBus usage.

SaaS profit example

Turn BrainBus usage into recurring revenue.

  • • Your SaaS plan: $49/mo.
  • • Average usage: 300 AI calls per month.
  • • Approx BrainBus cost @ ~$0.015/call: $4.50.
  • • You keep: ~$44.50 of the subscription before your own overhead.

Scale that across multiple apps or client accounts and BrainBus becomes a quiet, predictable cost line behind much larger revenue lines.

Studios & agencies

Resell AI without exposing raw model costs.

  • • Give each client or app its own BrainBus key.
  • • Track usage per key and bill however you like.
  • • Charge per seat, per project, or per AI call — BrainBus doesn’t get in the way.

You stay in control of client pricing; BrainBus just keeps the meter honest in the background.

Back-of-napkin forecast

Quick mental math before you commit.

  • • 1,000 calls/month ≈ $10–$20.
  • • 5,000 calls/month ≈ $50–$100.
  • • 20,000 calls/month still sits comfortably behind a few mid-tier SaaS plans.

Actual numbers depend on the mix of models used, but BrainBus is designed so your usage cost stays a small, predictable fraction of what you charge your own customers.

Trust, data, and due diligence

If you’re evaluating BrainBus as part of your startup’s AI infrastructure, you should understand how it behaves. BrainBus was built to be transparent by design.

  • Data handling you can reason about.
    BrainBus focuses on metadata: which app called which route, how often, and at what cost. Your upstream model providers handle the heavy lifting on prompt processing. BrainBus doesn’t try to turn your prompts into another opaque data product.
  • Separation of concerns.
    Application logic stays in your app. Model behavior stays with the AI providers. BrainBus stays in the middle, routing and metering. That separation keeps each layer easier to inspect and replace.
  • Built by a product studio, not a faceless reseller.
    BrainBus is developed and used by Venturelogix, a private product studio that builds and sells real AI ventures. The infra has to work in practice before it’s ever offered to anyone else.

For your checklist

  • • Clear API boundary and single endpoint.
  • • Per-app keys and usage for attribution.
  • • Model routing & pricing logic visible at config level.
  • • Simple architecture: web app + routing layer + upstream AI.

If you’d like a deeper architecture walkthrough as part of technical due diligence, BrainBus can be presented alongside your existing system diagrams so stakeholders can see exactly where it lives and what it touches.

Request a technical overview →