You will get DeFi Trading Bot - Real-Time Price Monitoring & Telegram Alerts
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Project details
The Te le gram Trading Bot is an automated system for early detection of newly launched tokens on the Solana blockchain, designed to surface high-opportunity and potentially suspicious trading activity in near real time. Built with FastAPI, PostgreSQL, and the Te le gram Bot API, the system integrates GeckoTerminal for pool and trade analytics and Solana RPC endpoints for on-chain transaction verification. A multi-tier detection framework reduces false positives while prioritizing speed and signal quality.
The bot operates across three detection tiers:
Tier 1 (0–60 seconds): Detects early anomalies based on token age, liquidity ($5k–$50k), and large initial buy patterns.
Tier 2 (1–5 minutes): Identifies early pump signals using trade velocity, buy/sell ratios, and wallet concentration analysis.
Tier 3: Ongoing monitoring of smart wallets and exit-risk indicators.
Key features include configurable filters to separate organic growth from manipulation, API caching and rate limiting, and interactive Telegram alerts with one-click trading actions. Tokens are processed every 30–60 seconds, with typical end-to-end alert latency of 30–90 seconds.
The bot operates across three detection tiers:
Tier 1 (0–60 seconds): Detects early anomalies based on token age, liquidity ($5k–$50k), and large initial buy patterns.
Tier 2 (1–5 minutes): Identifies early pump signals using trade velocity, buy/sell ratios, and wallet concentration analysis.
Tier 3: Ongoing monitoring of smart wallets and exit-risk indicators.
Key features include configurable filters to separate organic growth from manipulation, API caching and rate limiting, and interactive Telegram alerts with one-click trading actions. Tokens are processed every 30–60 seconds, with typical end-to-end alert latency of 30–90 seconds.
Programming Languages
PythonWhat's included
| Service Tiers |
Starter
$500
|
Standard
$1,500
|
Advanced
$3,000
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 15 days |
Number of Revisions | 1 | 2 | 3 |
Design Customization | |||
Content Upload | |||
Responsive Design | |||
Source Code |
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YT
Yohannes T.
Mar 8, 2025
Review sentiment Analysis using AI
The freelancer, Ganesh Verma, posted our proprietary product we hired them to build for sale on Upwork. They listed it as their own product and offered to sell it including the source code. This freelancer is associated with the agency Moogle Labs (https://www.upwork.com/agencies/1481912201822543872/). They are absolutely dishonest, stay away from them.
The project they signed up to complete in 4 months took more than a year. They oversold their capabilities. I had to hire two other freelancers to get the project to where it is. After all that, they stole our work and tried to sell it.
The project they signed up to complete in 4 months took more than a year. They oversold their capabilities. I had to hire two other freelancers to get the project to where it is. After all that, they stole our work and tried to sell it.
OB
Odusola B.
Sep 8, 2021
Frontend Developer needed for Web and mobile responsive website
Fantastic to work with
MN
Max N.
Oct 28, 2020
4 pages
The job was a success, Ganesh quickly understood what was expected and was able to deliver.
Highly recommend
Highly recommend
MN
Max N.
Oct 6, 2020
Looking for the best UI/UX / Web Designer on Upwork
MS
Mantas S.
Mar 16, 2020
UI redesign
About Ganesh
AI/ML Specialist | AI Automation | Data Scientist | Python Expert
100%
Job Success
Mohali, India - 8:41 am local time
🎯 𝐌𝐲 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞
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Steps for completing your project
After purchasing the project, send requirements so Ganesh can start the project.
Delivery time starts when Ganesh receives requirements from you.
Ganesh works on your project following the steps below.
Revisions may occur after the delivery date.
Token Discovery (Phase 1)
- Pulls trending / new Solana pools - Applies configurable filters on **age, price performance, liquidity, and volume** - Deduplicates tokens and stores them in the `tokens` / `tokens_less_age` tables for later analysis and backtesting.
Early Buyer Identification (Phase 2)
- For the discovered tokens, the `BuyerService` fetches the **first 20–50 buyers - These are stored in `early_buyers` and `current_buyers` with rich metadata: wallet, tx hash, timestamp, usd_amount, token_amount, profit fields, etc.