AI assistants and search decision

Titanos

A technical user can build the core listing-generation, image, and margin-simulator workflows, but cannot easily reproduce Titanos' marketplace data, multi-agent orchestration, and polished multi-marketplace integrations that justify the paid product.

Visit website
You pay

$79/mo

$948/yr

Read off the official pricing page.

You’d pay instead

$100one-off66 h to build

$200/mo6 h/mo upkeep

On cash alone, building overtakes the subscription at 3 seats.

No open-source build does this yet

Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.

What a replacement has to do

  • Connect a seller account, run product research, generate or edit listing text, generate listing images, simulate margins/fees, and push/save the listing.

What it still won’t have

  • Proprietary marketplace and market-volume data used for product research
  • Built-in multi-agent orchestration and pre-trained seller-specific agents
  • Polished, integrated Chrome extension and prebuilt flows for Mercado Livre/Shopee
  • Brazil-specific tax/legal validation and ongoing regulatory updates
  • Production-hardened scaling, storage and collaboration features from the vendor

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 3 seats.

Paid seatsseats

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
—

AI build —APIs + hosting —

Time you would spend

—

—

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a minimal self-hosted Titanos-lite: use Next.js (TypeScript) for frontend, Node.js + Express for API, Postgres for data, Redis for background jobs, and Docker for deployment. Implement: (1) session-based login and an admin UI to create/edit listings; (2) LLM integration endpoints (OpenAI-compatible) for listing text generation and revision; (3) image-generation integration endpoints (Stability or similar) with upload to S3-compatible storage; (4) margin/ROI simulator implementing Simples Nacional, NCM, and ICMS inputs and calculations; (5) background job worker for image generation and research tasks, with rate-limit handling and retries. Out of scope: marketplace-native connector implementations (full Seller Central OAuth flows), multi-marketplace sync, and curated market-data feeds. Include error handling, input validation, request rate-limit responses, unit tests for core logic, and CI/Docker deployment scripts.
How we checked3 sources · 3/3 runs agreed · evidence score 62

How the score was reached

  • Partly verdict base52
  • 3 cited sources+3
  • Price verified on pricing page+3
  • 3/3 assessment runs agreed+4
  • Evidence score62

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Cited sources · 3

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat recorded