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Case study · Trading / FinTech · United Kingdom

Trading CoPilot

Never miss a trade because you stepped away.

Real-time AI trading alerts and execution companion for forex traders.

Trading CoPilot product interface
Client
Private trading client
Industry
Trading / FinTech
Region
United Kingdom
Engagement
B2B · subscription SaaS · AI platform + web app
Overview

Trading CoPilot turns TradingView alerts into clear, real-time trade guidance. It sends each alert to the trader over messaging, waits for a yes or no, and executes the approved trade through a broker connection. A web dashboard keeps alerts, trades, logs, and settings in one place, plus a chat companion that knows the trade in front of you.

The challenge

The problem we set out to solve.

01

Traders missed good setups when work or life pulled them away from the screen.

02

The workflow was manual — screenshots passed from TradingView to chat to broker.

03

Too many low-quality alerts buried the signals that mattered.

04

Generic chatbots could not reason about a specific open trade.

What success needed to look like

  • A trader never misses a valid setup, even away from the screen.
  • Approve or reject a trade in one tap, from anywhere.
  • Only high-confidence alerts surface — the noise expires on its own.
  • Every alert, decision and trade is logged and auditable.
Our approach

How we delivered it.

01

Diagnose

Mapped the real workflow from TradingView alert to broker order — and pinpointed exactly where good setups were being lost.

02

Design

Designed the alert → approve → execute loop and the confidence-filtering rules together with the trader.

03

Build

A senior pod built the webhook listener, AI insight engine, messaging bot, broker connector and dashboard — tested against live alerts.

04

Launch

Shipped into live trading with real TradingView alerts and a connected broker, watched closely for the first sessions.

05

Run

Kept it running: filtering tuned to cut noise, logs monitored, and the companion chat sharpened as usage grew.

The solution

What we built.

We built a platform that ingests TradingView alerts through a webhook listener, enriches each one with AI insight, and messages the trader in real time. On a yes, it executes the trade through a broker connection and logs the result. The dashboard shows alert history, trades, and logs, while a companion chat answers questions about a specific alert or trade. Filtering rules prioritize accepted alerts and expire rejected ones, so noise drops fast.

Webhook listener for reliable TradingView alert ingestion
AI insight engine with rules-based validation and confidence guidance
Real-time messaging alerts with a fast yes/no reply
Broker execution connector with full trade logging
Trader dashboard for analytics, alert history, trades, and settings
Companion chat that attaches to a specific alert or trade
Filtering that prioritizes accepted alerts and expires rejected ones
Trading CoPilot dashboard with trade counts, alerts and volume charts
Trading CoPilot trades table with entry prices and win rate
How it’s built

Tech stack

ReactFastAPISupabase (PostgreSQL + RLS)Supabase Edge FunctionsOpenAI Responses APIAWS EC2

Integrations

  • TradingView Webhooks
  • OpenAI Responses API
  • Telegram Bot
  • cTrader broker integration

Security

  • OTP authentication with secure sessions
  • Row-Level Security for per-user data isolation
  • Encrypted API key storage in Supabase
  • Webhook authenticity validation, HTTPS-only endpoints
More from the build
Trading CoPilot dashboard at a trading desk
Trading CoPilot trade monitoring on a laptop
The takeaway

The hard part of a trading assistant is not the signal — it is acting on it reliably while the trader is away. We built the loop that closes that gap.

Start

Let’s build the one that runs after.

A senior engineer reads every brief, and your call gets scheduled within 24 hours.

What happens next

  1. 01

    You send a brief or book a call

    Two minutes, whichever you prefer.

  2. 02

    A senior engineer replies within 24 hours

    Not a sales rep.

  3. 03

    Honest scoping, in writing

    And if we’re not the right fit, we say so.

Abdul Basit, CEO of Hashlogics

“I started Hashlogics because too many teams ship a demo, get paid, and disappear. We build to a standard we’d run ourselves — and we stay to keep it running.”

Abdul Basit · CEO · a direct line

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