PennyGems API integration & OpenData services

Authenticated session mirror

We reverse engineer the PennyGems mobile authentication flow (device registration, token issuance, session refresh) and expose it as a typed server-side client. A downstream portfolio service can mint a session on behalf of an authorized user and reuse it for watchlist and ratings calls without forcing the user back into the app. Typical use: a broker's research portal that needs to surface a client's saved penny-stock picks inside its own dashboard.

Rating-change webhooks

Because PennyGems updates its Buy/Sell calls three times per trading session, batch polling wastes bandwidth. We wrap the refresh endpoint as a normalized webhook: every transition (for example Hold → Buy on ticker SNDL) is pushed as a JSON event with timestamps, previous rating, and confidence hints. Typical use: alerting an in-house trading Slack, or gating swing-trade entry rules.

Watchlist sync bridge

The watchlist holds ticker, sort preference, alert triggers, and daily performance snapshots. We mirror it into your system of record (Postgres, BigQuery, or a SaaS CRM) with conflict-safe upserts. Typical use: unifying a retail trader's PennyGems watchlist with their TradeStation or Interactive Brokers positions for a single blended PnL view.

Ratings-history backtester feed

A distinctive PennyGems feature is the multi-month history of its own ratings — users can audit how accurate past Buy calls turned out. We expose that time series as a flat CSV / Parquet feed indexed by (ticker, rating_date, rating_tier) so quant teams can regress it against actual price action or combine it with Alpha Vantage / Finnhub price history.

News story ingestion

The in-app news stream is AI-curated from dozens of business publishers. We normalize each item to {ticker, headline, publisher, published_at, canonical_url, summary}. Typical use: feeding an internal research wiki, or deduplicating stories already ingested from a Bloomberg or Reuters feed.

Export & reporting module

Any of the above data can be packaged into Excel, JSON, or PDF exports on a schedule. Typical use: month-end compliance archives, or investor-relations snapshots that log every rating change on a basket of micro-cap holdings. Outputs are tagged with source, retrieval time, and hash so downstream auditors can verify lineage.

1. Signal-to-execution bridge for a swing-trading desk

Context: A small swing-trading shop uses PennyGems as an idea generator and TradeStation or Interactive Brokers for execution.

Data / API involved: Ratings webhook for Grab/Buy transitions; watchlist sync for ticker allowlists; ticker detail bundle for pre-trade volatility and float checks.

OpenFinance mapping: PennyGems acts as the "signal producer"; the brokerage API (or a pay-per-call gateway we host) acts as the executor. Events flow signal → risk filter → order staging. Every rating change is persisted with source hash so post-trade compliance can trace the idea origin.

2. Retail wealth-app watchlist unification

Context: A consumer wealth app wants to let users import their PennyGems watchlist alongside holdings from Robinhood or a broker connected via Plaid-style aggregation.

Data / API involved: Authenticated session mirror, watchlist extraction API, ratings history for each imported ticker.

OpenData mapping: The integration looks like a classic OpenData feed — user authorizes, consent is logged, a read-only token is issued, and watchlist + ratings flow into the wealth app's canonical portfolio schema. No trading permissions are requested.

3. Quant research pipeline for micro-cap alpha

Context: A quant team wants to test whether PennyGems rating transitions have predictive power on next-day returns for stocks under $10.

Data / API involved: Ratings-history backtester feed (Parquet), ticker metadata, joined against Alpha Vantage or Financial Modeling Prep price history.

OpenFinance mapping: Outputs land in the team's research lake; downstream Jupyter notebooks compute information coefficients. We provide a stable schema and replay endpoint so the feature is reproducible across model retrains.

4. Investor-relations monitoring for micro-cap issuers

Context: An IR firm representing OTC / micro-cap issuers wants to track when PennyGems changes its rating on client tickers and what news stories the app is surfacing.

Data / API involved: Ratings webhook filtered by a ticker basket, news story ingestion, export module for weekly PDF reports.

OpenData mapping: Read-only ingest into the IR firm's existing media-monitoring stack. Each captured story includes canonical publisher URL so it can be cross-referenced against SEC EDGAR XBRL filings and FINRA OTC Transparency data for a fuller picture.

5. Educational & paper-trading platforms

Context: A trading-education product wants students to paper-trade against the same rating stream retail users see.

Data / API involved: Real-time ratings feed, ticker search, daily snapshot export for grading.

OpenFinance mapping: The education platform becomes a secondary consumer of PennyGems signals under a documented data-use agreement; we handle rate-limit shaping and user-level attribution so the source can validate traffic.

Auth & session bootstrap

POST /api/v1/pennygems/session
Content-Type: application/json

{
  "device_id": "dev-9f2c...",
  "app_version": "com.stockring.cheapstocks/2025.x",
  "auth": { "type": "user_consent_token", "value": "<USER_TOKEN>" }
}

200 OK
{
  "session_id": "sess_7h2k...",
  "expires_at": "2026-04-23T20:15:00Z",
  "scopes": ["watchlist:read", "ratings:read", "news:read"]
}

Watchlist + ratings fetch

GET /api/v1/pennygems/watchlist?sort=gain_desc
Authorization: Bearer <SESSION_ID>

200 OK
{
  "items": [
    {
      "ticker": "SNDL",
      "rating": "BUY",
      "rating_changed_at": "2026-04-23T14:02:00Z",
      "price": 1.84,
      "pct_change": 3.95,
      "volume": 21450000,
      "sparkline": [1.77,1.78,1.81,1.83,1.84],
      "market_cap_usd": 482000000
    }
  ],
  "paging": { "cursor": null }
}

Rating-change webhook

POST https://your-app.example/hooks/pennygems
X-PennyGems-Signature: t=1714060000,v1=9a...

{
  "event": "rating.changed",
  "ticker": "MARA",
  "previous": "HOLD",
  "current":  "BUY",
  "rated_at": "2026-04-23T18:30:00Z",
  "source":   "pennygems.mobile.v1",
  "trace_id": "01HV7..."
}

Signature validation uses HMAC-SHA256 over the raw body with a per-tenant secret. Replay protection via t timestamp window (default 5 min).

Ratings history export (CSV / Parquet)

GET /api/v1/pennygems/ratings/history
  ?ticker=SNDL
  &from=2025-01-01
  &to=2026-04-23
  &format=parquet
Authorization: Bearer <SESSION_ID>

# Columns:
# ticker, rated_at, rating_tier, previous_tier,
# intraday_slot (1|2|3), source_hash

Deliverables checklist

• OpenAPI / Swagger specification of the normalized PennyGems endpoints
• Protocol and authentication report (session lifecycle, token refresh, anti-abuse signals)
• Runnable source for watchlist, ratings, ratings-history, and news endpoints (Python or Node.js)
• Webhook sample with HMAC verification middleware
• Excel / CSV / Parquet export templates
• Integration test suite and sample fixtures
• Compliance notes: disclaimer propagation, retention, consent logging

Engagement models

• Source-code delivery from $300 — ready-to-run API source and documentation; pay after delivery upon satisfaction.
• Pay-per-call hosted API — call our managed endpoints and pay only for what you use; no upfront commitment, ideal for early-stage products.
• Retainer — monthly retainer for teams that need ongoing schema updates as PennyGems evolves.

About our studio

We are an independent technical studio focused on app-interface integration, authorized API integration, and OpenData / OpenFinance delivery for global clients. Our engineers come from fintech backends, mobile reverse engineering, and data-pipeline work; we have shipped production integrations for banking, brokerage, e-commerce, travel, and social apps. For PennyGems specifically, our edge is understanding both the micro-cap data domain and the mobile session model that produces it — we can move from "can this be integrated?" to a compliant, documented API without the client having to do the reverse engineering themselves.

• Protocol analysis, session modelling, and token lifecycle design
• OpenAPI-first delivery with typed Python / Node.js / Go clients
• Cloud hosting patterns (webhook fan-out, schedulers, Parquet lakes)
• Security reviews, consent logging, and retention policies
• Transparent pricing: source code delivery from $300, or pay-per-call hosted API

Contact

Share the target app and your integration requirements and we will scope it within one to two business days.

Contact page

Typical response time: under 24 hours on business days. NDA available on request.

Engagement workflow

1. Scope confirmation — which endpoints (watchlist, ratings, news), which export formats, and which compliance surface.
2. Protocol analysis and API design (typically 2–5 business days).
3. Implementation and internal validation (typically 3–8 business days).
4. Documentation, OpenAPI spec, sample clients, and test cases (1–2 business days).
5. First delivery in about 5–15 business days; edge cases and third-party approvals can extend timing.

FAQ

What do you need from me to start?

How long does a first drop usually take?

How do you handle the app's disclaimer?

Do you support pay-per-call pricing?