Step 1
Requirements Analysis
All case studies
Trading Automation - From Telegram Signals to Automated Execution
Impact We Have Created Together
- Manual trading reduced
- Execution errors minimized
- Faster trade reactions
- Scalable platform enabled
When We Joined
We joined at the concept stage and supported the project from system design through implementation, deployment, and ongoing support.
Who This Is For
Founders and product teams that require automated signal ingestion, secure execution, mobile first decision flows, and compliance ready audit trails.
Duration:
3 months, Partnership ongoing
Tech stack:
626
Views
Our role
End to end platform development including architecture, automation, mobile app, backend orchestration, and operational tooling.
Anonym
Founder
- Idea
- Solution
- Key components
- Development Process
- Technology & Integration
- Main Features
- Main Challenge
- Advice We Give
- Most Special Step
Our role
End to end platform development including architecture, automation, mobile app, backend orchestration, and operational tooling.
Idea
The client operated a private Telegram based trading signal service that relied heavily on manual interpretation and execution.
Signals arrived in inconsistent formats and executing them manually was error prone and slow.
The idea was to transform this workflow into a scalable product that automatically extracts structured trading signals, delivers them to users in real time, and enables direct execution through connected trading platforms.
Security, reliability, and traceability were essential to protect both users and the business.
Solution
We designed and built a full trading automation platform consisting of a signal ingestion layer, parsing and validation services, a mobile app, an execution engine, and an admin control plane.
Trading signals are automatically captured from Telegram, normalized, and stored securely.
Users receive signals in a mobile app and can execute trades with controlled risk settings.
Orders are placed through exchange APIs, logged, reconciled, and reported, ensuring transparency and auditability across the system.
Key components
Development Process
Step 2
Design and R&D
Step 3
Implementation
Step 4
Quality Assurance
Step 5
Deployment and Support
We analyzed Telegram message patterns, execution workflows, user actions, and risk rules. Edge cases such as corrected messages and multi target signals were documented.
A compact, speed focused UX was designed in Figma. In parallel, ingestion and parsing approaches were researched and validated.
Backend services for ingestion, parsing, execution, and administration were built. The Flutter mobile app was implemented using MVVM and repository patterns.
We conducted parser unit tests, exchange sandbox testing, concurrency tests, and UX validation under load and failure scenarios.
CI/CD pipelines were set up, monitoring enabled, and long term support provided including updates and enhancements.
Technology & Integration
Technology
Product Design
Figma for product redesign and design systems.
Mobile Apps
Flutter for iOS and Android using a single codebase.
Back-End
Custom back-end development for business logic and integrations.
Admin Panel
Custom admin panel for managing the entire platform.
Integrations
- Telegram Bot API
- Exchange APIs (Bitget)
- Push Notifications
- Microsoft Azure Key Vault
Main Features
Automated Telegram Signal Ingestion
The platform continuously monitors a private Telegram channel and captures new messages in real time.
Messages are queued and processed regardless of format, including text, multi line posts, images, and pinned summaries.
A hybrid parsing approach extracts trading pairs, direction, prices, stop loss, take profit levels, allocation, and notes.
Parsed signals are validated and enriched before being stored securely with full traceability.
Mobile Trading App
The mobile app presents each signal in a clear, action focused layout.
Users can quickly understand the trade and decide to skip or execute. Push notifications alert users instantly when new signals arrive.
Execution flows allow controlled adjustments while keeping friction minimal and clarity high.
Secure Execution Engine
The execution engine validates user risk limits, computes required order structures, and places trades via connected exchange APIs.
Idempotent execution prevents duplicate orders and handles partial fills, retries, and exchange specific behavior.
All actions are logged with immutable timestamps to support audits and dispute resolution.
Admin Panel and Signal Control
Administrators can review parsed signals, correct extraction errors, manage exchange configurations, and control risk parameters.
Signal queues, confidence metrics, and logs help continuously improve reliability and quality.
Sandbox and Analytics
Sandbox modes allow testing without financial risk.
The system tracks latency, execution success rates, and signal outcomes, supporting product optimization and business decisions.
Main Challenge
The main challenge was transforming noisy, unstructured Telegram messages into reliable, executable trade signals while maintaining safety and performance.
Message formats varied widely and execution carried real financial risk.
We combined deterministic parsing with adaptive logic, implemented idempotent execution flows, and built per exchange adapters to handle inconsistencies.
Security and latency had to be balanced carefully to ensure fast delivery without compromising control or traceability.
What We Learned
We learned that automation in financial systems requires conservative defaults, strict validation, and detailed logging. Reliability matters more than speed alone.
Why This Matters for Our Partners
These learnings help partners build trading platforms that scale safely, reduce operational risk, and meet compliance expectations from day one.
Our Advice
If your product executes financial actions, design idempotency, auditability, and risk controls as core features rather than add ons.
Most Special Step
The most special part of this project was bridging unstructured social trading signals with institutional grade automated execution.
Combining intelligent parsing, human correction paths, and a secure execution engine made it possible to move from Telegram messages to verified trades within seconds.
The integration of Azure Key Vault ensured that sensitive credentials were protected while still enabling real time execution.
This fusion of automation, security, and human oversight created a system that feels simple to users while handling extreme complexity behind the scenes.
It allows the platform to scale confidently without increasing operational risk or manual supervision, even as signal volume, user activity, and exchange integrations continue to grow over time.
Behance
Anonym
Founder
5.0
What started as a manual Telegram-based service was transformed into a secure, scalable platform. The team handled complexity, security, and traceability with a high level of professionalism. The result gave us confidence to grow the business sustainably.
Other References
Every successful project leaves behind measurable results and a clear path forward.
The references below show how we work, what we deliver, and the outcomes our partners achieve with us.
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Frequently Asked Questions Before Collaboration
Vitec transformed a manual, Telegram-based trading-signal service into a secure platform where signals are automated and users trade with one tap.
Manual trading steps were eliminated and trade execution became faster and more reliable.
Vitec took end-to-end responsibility from concept and design to development and ongoing support. Mobile apps, backend, and admin panel with automated signal processing.
Yes. Vitec builds a fintech trading app end to end for startups and established companies - from strategy and design to development and long-term support. Trading App is one example; we can do the same for your product.
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