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Daedalus Grid

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Own the hardware, rent it, or pay per use? Plan the right way to run AI in your business.

Daedalus Grid compares every way to run AI — owning GPUs, renting them, serverless GPUs, managed endpoints and per-token APIs — and recommends the set-up that fits your scale, data sensitivity and budget. Plain business questions, a costed answer in minutes.

Start planning → See how it works

Free · No sign-up · Runs entirely in your browser

Compared across six architectures
  • Owned GPU
  • Rented GPU
  • Serverless GPU
  • Managed endpoint
  • Open-model API
  • Frontier API

How it works

From use case to architecture in three steps

No technical knowledge required. Answer in plain business terms; the engine does the modelling.

  1. Describe your use case

    What the assistant should do, who uses it and the quality bar — in plain language.

  2. Add scale, data & compliance

    Volumes, growth, document sources, data sensitivity and the regimes you fall under.

  3. Get a ranked recommendation

    A best-fit architecture with cost, energy, break-even and the compliance flags that apply.

Under the hood: compliance gates → sizing → cost & energy → a transparent score. Deterministic, with every assumption shown.

What you get

A complete build picture — not just a model name

Every recommendation comes with the numbers and caveats you need to defend the decision.

  • Ranked architectures

    All six options scored for your case, with clear pros, cons and trade-offs.

  • Cost & unit economics

    Monthly ranges plus €/request and €/seat, so finance can sign off.

  • Energy & carbon

    kWh and kg CO₂e per month, with an honest measured-vs-estimated basis.

  • Break-even & payback

    The token volume where renting beats APIs, and a 3-year buy-vs-rent payback.

  • GDPR & EU AI Act flags

    Residency, special-category and transparency duties surfaced with current dates.

  • RAG & tooling fit

    Retrieval sizing and connectors to your existing tools, noted as an MCP integration.

The options

Six ways to run an LLM — compared honestly

Each has a sweet spot. The planner finds yours; here's the shape of the field.

  1. Owned GPU

    Buy the hardware. Lowest cost at high, steady volume; you own the capex and the ops.

  2. Rented GPU

    Dedicated GPU-hours in the cloud. Managed compute without the capital outlay.

  3. Serverless GPU

    Scale-to-zero open-model GPUs billed per second. Wins on spiky or low volume.

  4. Managed endpoint

    In-tenant endpoints (Bedrock, Azure, Vertex). Your cloud, your data boundary.

  5. Open-model API

    Open models behind a per-token API (Together, Groq). No infrastructure to run.

  6. Frontier API

    Closed frontier models per token. Top quality, fastest to start, least control.

Private by design — your data stays yours

The recommendation is computed in your browser, so your answers never leave your device while you plan. They are sent only if you explicitly save a shareable link or request the full report by email — both opt-in, both explained in our privacy notice.

Read the privacy notice →

FAQ

Questions, answered

Is it really free?

Yes. Daedalus Grid is a free planning tool from Ozymind. There is no sign-up to use it; you only share contact details if you ask us to email you the full report.

Do you store my answers?

Not while you plan. The engine runs in your browser and your answers stay on your device. They are sent to us only if you explicitly save a shareable link or request the full report.

How accurate are the cost estimates?

Costs are shown as ranges, built from vendor pricing we verify on a regular cadence, with every assumption visible. Treat them as a well-grounded first pass for comparison — not a quote.

What are the six architectures?

Owned GPUs, rented GPUs, serverless (scale-to-zero) GPUs, managed in-tenant endpoints, open-model per-token APIs and frontier per-token APIs. The planner ranks all six for your case.

Is this legal or financial advice?

No. The GDPR and EU AI Act flags and the cost figures are guidance to inform a conversation with your own legal, security and finance teams — not a substitute for professional advice.

Who is behind it?

Ozymind, a data & AI engineering studio. We built Daedalus Grid to make the build-versus-buy decision transparent — and we can help you implement whichever path you choose.

Can I save or share my plan?

Yes. Save a plan to get a private, shareable link, or request the full report by email. Re-opening a link recomputes the result in your browser against the current catalog.

Should we buy GPUs or rent them?

A decades-old rule works remarkably well: pay as you go until what you have spent renting roughly matches the purchase price, then buy. Followed blindly, that never costs more than about twice what perfect foresight would have spent on the choice — and no fixed plan can promise better without knowing the future. The planner computes your switch month from your own numbers, shows every assumption behind it, and lets you pull the switch earlier if you trust your demand forecast.

Plan your LLM build with confidence

Get a defensible, architecture-first recommendation in minutes — cost, compliance and carbon included.

Start planning →

Prefer to talk it through? Ozymind can validate your plan and build it with you. Talk to Ozymind →