58
Oigetit Fake News Filter
Oigetit Fake News Filter is an Android app from Oigetit, Inc. in the News & Magazines category, currently rated 4.4★ across 632 ratings. Initial signal reads as largely positive sentiment, users highlighting consistency and feature depth.
Quality Score is 58: Solid (established niche player). For a News & Magazines app, that means established niche player. The full BU Investment Matrix below scores 8 dimensions including monetisation, growth, and operational risk.
Track changes month-over-month in the Performance section below: live snapshot history and revenue forecast included.
Free AI audit of this app’s store listing
- Title & subtitle keyword fit
- Description hook & conversion structure
- Screenshots, ratings, reviews strategy
📊 Performance Tracking LIVE
Synthetic estimate. Inputs: category complexity, file size, screen count, monetization layer, platform reach, age × team-size proxy. Calibrated against 2024-2026 indie-agency rate surveys. Full math + source list on /methodology.
| 🧱MVP baseline (design + 1-store ship) | +$28K |
| 📱5 unique screens × $4.5K | +$22K |
| ⚙News & Magazines complexity ×1.20 | +$10K |
| 🌐Cross-platform reach (iOS + Android) | +$33K |
| ⚙7.1y maintenance × ~1-person team | +$42K |
Synthetic estimate from ratings × category benchmarks. Calibrated against 2024-2026 mobile-attribution retention + DAU/MAU reports. Numbers are US-storefront-equivalent — true global audience can be 5-10× larger for international apps. Full math + source list on /methodology.
| 📲News & Magazines engagement | ~120 installs / rating |
| 📅7.1y of rating accumulation | -30% |
| 🔁News & Magazines D30 retention | 15% |
| 📍DAU / MAU stickiness | 0.45 |
Heuristic guess from app bundle size, category, store description signals, and release-date stack era. Bumetric does not disassemble binaries — for binary-level certainty you would need an SDK intelligence tool or the manifest itself. Reasoning chain on the right. Full ruleset on /methodology.
| 🏷Category context | News & Magazines |
| 📦Compact Android bundle | → Native Kotlin |
Heuristic risk score from time-since-last-update + ratings velocity proxy + Editor's Choice / curated featuring signals. Calibrated against 2024-2025 app-store ranking decay reports. Not a guarantee — a quiet app with a healthy codebase looks the same as an abandoned one until something breaks. Full math on /methodology.
| 📅31 days since last update | Healthy release cadence |
How we forecast this revenue
LOW CONFIDENCEBU Investment Matrix
Early-stage solo · 40/100INDIE TIERexpected for tier- 💰 Revenue: Marginal — $200 - $1250/mo · INDIE tier · medium confidence, trajectory unclear.
- ⭐ Quality: 4.4★ across 632 reviews — solid.
- 📍 Market: Not yet charting in any of the 9 monitored markets.
- 📈 Growth: Insufficient signal to assess trajectory.
- ⚠️ Risk: Low — no material risk signals detected.
💰 Forecast Revenue / mo
MODEL| Good rating (4.4★)METRIC | +$800 | |
| Established app (7y old)METRIC | +$800 | |
| Ad-supported / freemiumMETRIC | +$600 | |
| Early-stage install base (632 ratings)METRIC | +$400 |
📈 Reviews Growth
LIVE⭐ Rating Trend
LIVE📝 About this app
With OIGETIT, deciding the trustworthiness of news articles is no longer an issue! Our mission is to eliminate the time you spend reading fake news. Instead, Oigetit brings the trust back into news articles. In the past, you may have received your news from maybe 8 to 10 news sources network TV, and maybe US and local papers too.… View full description on the official store →
Tech & Domain Intel — oigetit.com
- Mail provider
- Google Workspace
- Tech stack
- Google Workspace
Track this app’s revenue
FREEProfile & Insights
Identification
- App name
- Oigetit Fake News Filter
- Developer
- Oigetit, Inc.
- Bundle ID
- io.scal.oigetit
- App Store URL
- Open in App Store
- Category
- News & Magazines
- Content rating
- Not found
- Languages
- Not found
Company
- Website
- www.oigetit.com
- Tagline
- Not found
- Description
- Not found
- Founded
- Not found
- HQ / Address
- Not found
- Employees
- Not found
- Logo
- Not found
Revenue
- Verified revenue / mo
- Not found
- AI revenue estimate / mo
- Not found
- AI annual estimate
- Not found
- ML model estimate / mo
- $357/mo
- Top-grossing rank
- Not found
- All-time revenue
- Not found
- Pricing
- Not found
