AI-driven lead scoring
Automated prioritisation so the team works the highest-potential leads first, with the pipeline tracked in real time.
Sales · AI lead scoring
AI Lead Management CRM
A custom lead management system with AI lead scoring, built to replace a legacy platform that had become inflexible and insecure. Sales teams see the leads most likely to convert first, and the data came across from the old system intact.
Client
A CRM provider
Shape
AI scoring plus CRM
Hosting
AWS serverless
Hard part
The migration
Status
Running and supported
The problem
What it replaced.
The client's legacy lead system could not be extended, was hard to secure and made every integration risky. Sales teams worked leads in the order they arrived rather than the order they were likely to close.
What we built
The pieces, and why each one exists.
Serverless endpoints on AWS Lambda
Scales with transaction volume without a server fleet to manage.
APIs and call transfer
Custom APIs and Twilio integration connect the CRM to the client's communication tools, including live call transfer.
Security and data integrity
Encryption, access controls and validation throughout, so lead data stays accurate and protected during and after the migration.
The hard part
Where the time actually went.
The legacy platform's architecture made migration the riskiest part. Lead history is the sales team's memory, and losing or corrupting it would have undone the point of the project, so the migration was planned, validated and reconciled before cutover.
What we took from it
Carried into later work
- Migrate and reconcile before you switch anything off.
- Scoring helps only if the team trusts it, so it has to be explainable.
The stack
What it runs on.
Backend
PythonDjangoAWS Lambda
Frontend
ReactJS
Integrations
Custom APIsTwilio call transferExisting CRM tools
Security
EncryptionAccess controlsData validation
Worth knowing
No client name, and no numbers we cannot show.
The client asked not to be named. We have not put improvement percentages on this page; we can arrange a reference conversation, with the client's agreement, for work like yours.
Building something like this? See how we work as an AI implementation partner.
Next step
Bring us the problem, not the spec.
Thirty minutes. If your problem rhymes with this one we will say what we would do differently the second time.