Social media decision
Tokfluence
Build a small, self-hosted influencer index and API for niche use cases is feasible for a technical person, but reproducing Tokfluence's 15M+ first-party index, verified email coverage, low-latency scale, and campaign-tracking features is impractical without substantial data and infrastructure investment.
Visit website↗$49/mo
$588/yr
Read off the official pricing page.
$100one-off160 h to build
$300/mo6 h/mo upkeep
On cash alone, building overtakes the subscription at 7 seats.
The code exists. It is not what you are paying for.
These 2 projects are real, published, and do the core job — and this page still says keep paying. What the subscription buys is proprietary data, infrastructure at scale and proprietary data, and none of that ships in a repository. Fork one anyway if you want to. Go in knowing what it does not carry. What stays hard ↓ · All Tokfluence alternatives, with the arithmetic →
What a replacement has to do
- Index TikTok profiles, extract contact emails, expose search & semantic discovery, return profile and post analytics via a REST API, simple campaign tracking and CSV export.
What it still won’t have
- A 15M+ first-party, deduped and continuously refreshed global index
- Verified email coverage at Tokfluence scale (10k+ reveals/month) and the Pro credit/pricing model
- Sub-100ms response latency from a prebuilt search index
- Built-in campaign tracking, analytics, and priority support
- Legal/operational handling of scraping risk and scale (disclaimer notes Tokfluence is unofficial)
What remains hard
- Proprietary data
15M+ first-party index
- Infrastructure at scale
<100ms Typical response latency
- Proprietary data
Creator contact emails included
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 7 seats.
Money you would actually spend
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
Build a minimal TikTok influencer search API and dashboard using: Python (FastAPI) backend, Postgres for profiles, Redis for job queue, Milvus or Pinecone for embeddings, and React for a tiny dashboard. Core features in scope: (1) crawler that pulls public TikTok profile & post pages and writes normalized profile records with last_updated and public contact_email, (2) dedupe and simple indexing into Postgres + vector DB, (3) REST API endpoints: GET /v1/creators (filters + paging), GET /v1/creators/{handle}, POST /v1/posts/batch (job + poll), POST /v1/semantic_search (use OpenAI or local embeddings), credit-accounting header X-Credits-Remaining, and simple CSV export, (4) a single-page dashboard for searching, saving lists, revealing emails (consumes API), and exporting CSV, (5) tests for crawler, API handlers, and semantic endpoint plus error handling, retries, and health checks. Out of scope: scaling to 15M creators, global deduplication at scale, priority SLA, and legal/compliance protections for high-volume scraping.How we checked
How the score was reached
- Pay verdict base20
- An open-source build was found+5
- 5 cited sources+3
- Price verified on pricing page+3
- 3/3 assessment runs agreed+4
- Hard moats found in the evidence-6
- Evidence score29
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.
- official productTokfluence home
- official pricingTokfluence pricing
- official docsTokfluence API
- open sourceqeeqbox/social-analyzer
- open sourcesherlock-project/sherlock
Integrity checks
What held up, and what did not.
