Social media decision

Ocoya

A technically capable developer can build a useful subset (AI captioning + scheduling + basic publishing) in a week and run it cheaply; reproducing Ocoya's full product (proprietary dataset-driven predictions, many integrations, enterprise polish, and scale claims) is much larger and better left to the vendor.

Visit website
You pay

$15/mo

$180/yr

Read off the official pricing page.

You’d pay instead

$50one-off30 h to build

$50/mo6 h/mo upkeep

On cash alone, building overtakes the subscription at 4 seats.

Open-source builds that already do this

Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All Ocoya alternatives, with the arithmetic →

What a replacement has to do

  • Generate social post copy with an LLM, attach/upload media, schedule posts to connected social accounts, and persist assets & schedules.

What it still won’t have

  • AI agent templates and built-in automations/workflows
  • Large set of integrations and design plugin ecosystem (Canva, Unsplash, Giphy)
  • Proprietary analytics trained on Ocoya's dataset and best-times predictions
  • High-throughput scheduler claimed at product scale (eg. 'a thousand posts per minute')
  • Multi-workspace enterprise controls, approvals, and client-facing collaboration polish

What remains hard

  • Proprietary dataTrained on over 20M data-points
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 4 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 AI-driven social post scheduler using Next.js (React) frontend, Postgres, Redis, and a Python (FastAPI) backend. Implement: user auth (email), workspace and single-user support, media upload to S3-compatible storage, LLM caption-generation endpoint (pluggable, default OpenAI), per-request credit accounting, OAuth connectors for at least Twitter/X and Facebook/Meta to publish posts, a job scheduler (Redis + RQ/Celery) to execute scheduled publishes, and a calendar view to create/edit/schedule posts. Exclude: multi-tenant enterprise roles, advanced analytics, many third-party design integrations, and AI agent/workflow builder. Provide error handling for failed publishes, webhook retry logic, unit and integration tests for API endpoints and scheduler jobs, and Docker-compose for local dev plus deployment instructions for a single VPS or managed cloud (Postgres, Redis, object storage).
How we checked5 sources · 2/3 runs agreed · evidence score 60

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 5 cited sources+3
  • Price verified on pricing page+3
  • Hard moats found in the evidence-3
  • Evidence score60

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 · 5

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page! 2 of 3 runs agreed; the verdict is the majority✓ Citations limited to fetched pages! 1 moat quoted from the page