Reaching the scores, sentiment, and alerts behind AI Crypto Scanner - Bitcoin

The scores this app shows on a phone are computed on its servers and handed back on request, not derived locally. That single fact is what makes it integrable: a third party can mirror the technical evaluation, the six-level futures-sentiment read, and the price-alert triggers without re-implementing every indicator from raw candles. The harder half of the job is freshness. A score is a snapshot, sentiment decays on the funding clock, and the long/short ratios the app leans on are only kept for a short window upstream — so the integration is really a reconciliation problem as much as a data-pull, and that is where most of our build time goes.

Bottom line: route the build through the app's own client-to-server traffic for the scores and sentiment labels, then reconcile against documented Binance and Coinbase market data so the numbers can be trusted and back-filled. The per-user alert thresholds come through a consented session. Nothing here needs the app to be reverse-engineered against its users — it is interface mapping for interoperability, run against a consenting account or a captured session arranged with you.

Data the scanner produces, and where it comes from

These are the surfaces worth pulling. Each maps to something a user already sees in the app.

Getting to the scores and sentiment feed

Three routes apply to this app. They are not mutually exclusive — a real build usually uses two of them together.

1 — Authorized interface mapping of the app's traffic

The scores, the scan results, and the sentiment labels all arrive over the app's own client-to-server calls. Mapping those calls reaches the derived data directly, in the exact shape the app uses. Effort is moderate; durability is tied to the app version, so we re-validate the mapping when JejuLeadSoft ships an update. This is the spine of the integration for everything the app computes itself.

2 — Consented session for per-user state

Alert thresholds and any account-bound settings live behind a user session. With a consenting account those become readable and syncable. Effort is low to moderate, depending on the token scheme; we handle the session capture and refresh as part of the build.

3 — Upstream exchange-feed reconciliation

The app is built on Binance and Coinbase market data and Binance Futures derivatives data, all of which are documented and stable. Pulling the same raw klines, funding rates, and long/short ratios lets us verify the app's derived scores and backfill history the app does not retain. Effort is low; durability is high. We recommend pairing this with route 1 so the derived feed always has a ground truth to check against rather than standing alone.

What lands in your repository

The headline deliverable is code that runs, not a binder. For this app that means:

• Runnable clients (Python and Node.js) for the scan/score endpoint and the futures-sentiment lookup, with the auth/session handling already wired in.
• A reconciliation job that cross-checks each derived score against the matching Binance or Coinbase market data on a freshness window you configure.
• An alert bridge that turns the app's upper/lower price triggers into events your system consumes — deliverable on its own if that is all you want.
• An automated test suite built on recorded fixtures of real responses, with schema assertions so a changed field shows up as a red test rather than a quiet mismatch.
• A normalized schema so score, sentiment, and alert records land in one consistent shape keyed by exchange, symbol, and interval.

Alongside the code you also get the OpenAPI/Swagger description of the mapped surfaces, a protocol and auth-flow report covering the token and session chain as it actually behaves here, interface documentation, and PIPA-aligned data-retention notes. Those matter, but the code is the thing you run on day one.

Shape of a scan request

Illustrative only — paths and field names are confirmed against the live traffic during the build, not copied from any document. The first block is the app's own surface; the second is the exchange-feed anchor that keeps it honest.

# 1) The app's derived read, returned on request
GET /scan/score?symbol=BTCUSDT&interval=4h
Authorization: Bearer <device-session-token>

200 OK
{
  "symbol": "BTCUSDT",
  "exchange": "binance",
  "interval": "4h",
  "technical_score": 72,                 # the app's 0-100 evaluation
  "summary": "MACD breakout, RSI cooling",
  "indicators": { "rsi": 58.4, "macd_hist": 11.2, "ma_cross": "golden" },
  "futures_sentiment": "Slightly Bullish",   # one of six buckets
  "as_of": "2026-06-15T08:00:00Z"
}

# 2) Reconcile the sentiment bucket against the raw ratio Binance publishes.
#    Long/short history is retained only ~30 days upstream, so backfill is bounded.
GET https://fapi.binance.com/futures/data/globalLongShortAccountRatio?symbol=BTCUSDT&period=4h
# -> [{ "longShortRatio": "1.84", "longAccount": "0.64", "shortAccount": "0.35", ... }]
# Watch the X-MBX-USED-WEIGHT-1M header; a 429 means back off before it turns into a 418 ban.

The normalized record we hand back collapses both into one row, so a consumer never has to know which call produced which field.

Freshness, decay, and reconciliation

This app's value is timeliness, so the integration is designed around how fast each surface goes stale. Three constraints drive that design:

• Scores are point-in-time. A score fetched at 08:00 describes 08:00. We stamp each record with as_of and let the consumer decide its own polling cadence rather than pretending a cached score stays current.
• Funding moves on an 8-hour clock. The sentiment read leans on Binance Futures funding rates, which settle on roughly an eight-hour cycle; sampling faster than that buys nothing, and we set the default cadence accordingly.
• Long/short history is short-lived upstream. Binance retains only about the last 30 days of the global long/short account ratio, so any backfill request that reaches past that window comes back empty. We scope the reconciliation window to that limit instead of letting it fail silently.

The reconciliation job is the safety net: when the app's derived score and the raw indicators disagree beyond a tolerance, that row is flagged for review instead of being trusted blindly.

Privacy footing and consent

JejuLeadSoft is a South Korean developer, so the governing privacy regime is the Personal Information Protection Act (PIPA), enforced by the Personal Information Protection Commission (PIPC). PIPA is among the stricter regimes globally, and a February 2026 amendment reported by Hunton raised the ceiling for severe-breach fines, so data minimization is not optional posture for us — it is how the work is scoped.

The good news for this app: the personal data footprint is light. A device push token and the user's own alert thresholds and watchlist criteria are the sensitive parts; the market data itself is not personal. We work against a consenting account or a session you authorize, log what is accessed, keep only the fields the integration needs, and operate under an NDA where the engagement calls for one. Consent scope, expiry, and revocation are documented with the build so the access path is auditable end to end.

What we plan around in this build

Two things about this app shape the engineering, and we account for both rather than handing them to you as homework.

• The six sentiment levels are the app's own bucketing. "Neutral" or "Slightly Bullish" are labels the app derives from long/short and funding data, not raw numbers. We map that bucketing explicitly so a label reconciles to the underlying ratio, and a consumer can choose to keep the label, the ratio, or both.
• It spans multiple exchanges and both spot and futures. A BTC score from Binance spot and one from Coinbase are different rows, and futures sentiment is a separate axis again. We key every normalized record by exchange, symbol, and interval so nothing is silently merged, and we capture the exact indicator period lengths the app uses so a reproduced RSI or MACD matches its screen.

Access to the account or session is arranged with you during onboarding; the build then runs against a consenting account or a captured session, and we re-validate the mapping after each app update so the feed does not drift.

Screens we worked from

Public store screenshots, used to confirm the surfaces named above. Select one to enlarge.

Where this sits among similar tools

Other apps in the same category hold comparable server-side state, which is useful when a client wants one unified feed across several scanners rather than a single source.

• TradingView — a crypto screener with 100-plus indicators that keeps saved screens, watchlists, and alerts server-side.
• altFINS — screens roughly 2,900 coins on RSI, MACD, ADX, and moving-average filters and stores user-built screens and chart setups.
• Cryptolume — an alert service for RSI, MACD crossovers, and volume spikes, holding each user's alert rules in its backend.
• DYOR — a multi-timeframe screener with RSI, MACD, Supertrend, and Bollinger filter groups plus saved strategies.
• Moondrops — an AI screener with 40-plus indicator filters and market-insight outputs tied to a user account.
• 100eyes — a scanner for RSI divergences and support/resistance zones that pushes alerts to subscribers.
• Altrady — a trading platform whose TA scanner add-on stores RSI, MACD, and Bollinger conditions per user.
• Gainium — a free screener with bot tooling that holds strategy configs and portfolio state.
• CoinScreener — an AI trading-signal service that keeps signal history and user preferences server-side.

What we checked, and where

The surfaces above were confirmed against the app's store listings and the documented exchange feeds it is built on, checked June 2026. Primary sources: the Google Play listing for the feature set and developer; Binance's long/short ratio and spot market-data documentation for the reconciliation anchors and the 30-day retention limit; and the PIPA overview for the privacy footing. A second iOS listing exists under App Store id 6452911458.

OpenFinance Lab — interface mapping, June 2026.

Questions we get about this one

How fresh is the score and sentiment data once the integration is running?

Scores come back point-in-time when you request them, so cadence is yours to set; most setups poll on the same rhythm the app refreshes. The futures-sentiment inputs move on Binance's eight-hour funding cycle, and long/short history is retained for roughly the last 30 days upstream, so we design the backfill window around that limit rather than assuming older ratios are still fetchable.

Will the reproduced technical scores line up with what the app shows?

They line up when the indicator parameters match. The app's RSI, MACD, moving-average, and Bollinger settings have specific period lengths, and its sentiment label is a six-level bucketing of long/short and funding data; we capture those exact parameters during the build so a score we hand back reconciles to the one on the app's screen instead of drifting.

Which exchanges and instruments does the data cover?

Spot prices and indicators draw on Binance and Coinbase, and the market-sentiment read uses Binance Futures long/short ratios and funding rates. Each normalized record is keyed by exchange, symbol, and interval, so a Bitcoin score sourced from Binance is never silently merged with a Coinbase one.

We only want the price-alert triggers, not the full scanner. Can you deliver just that?

Yes. The bridge that turns the app's upper and lower price triggers into events your own system consumes is a standalone deliverable; you do not have to take the scoring or sentiment pieces to get it.

Commissioning a build

Source delivery starts at $300: you get the runnable Python and Node.js clients, the reconciliation job, the test suite, and the docs, and you pay only after it is delivered and you are satisfied. If you would rather not host anything, the same scan, sentiment, and alert surfaces are available as a pay-per-call hosted endpoint with no upfront fee. A first drop usually lands in one to two weeks. Send the coin set and the surfaces you care about and we will scope it — or just tell us what you need and we will take it from there.