Dev tools · HR tech · AI
React · Node.js · ML · Serverless
2021 — V1
From zero, self-assessment platform
A fair scoring system for an unfair-by-default category
Two developers can do similar work and look identical from the outside. The hard problem was making the differences measurable in a way both sides could trust.
Software engineers leave digital footprints across the platforms they use. The challenge was finding a fair system to measure those footprints in a way that was both meaningful and applicable to all developers, regardless of the kind of work they do.
The scoring couldn't game easily, couldn't disadvantage developers who work on private codebases, and couldn't reward only the loud personas of open-source. It had to feel like measurement, not surveillance, and the patterns had to be defensible to both the developer being scored and the employer reading the score.
And it had to scale. Every new integration added complexity, so the architecture had to absorb that complexity without dragging the rest of the system down.
A self-assessment platform with ML at the core
Multi-source data, a privacy-respecting integration model, and a serverless backbone designed for the long game.
Multi-Source Data Pipeline
Integrations with the platforms developers leave digital footprints on. The pipeline that turns raw activity into measurable signal.
ML-Powered Scoring
Machine learning models trained to find patterns in developer activity and translate them into fair, defensible scores.
Self-Assessment Flow
Developers connect their accounts and see their score across categories. Personal insight first, hiring tool second.
Strengths & Gaps View
The platform surfaces where a developer shines and where they could grow. Useful for the developer, valuable for their next employer.
Serverless Architecture
Built on AWS serverless so the platform handles bursty integration loads without paying for idle compute.
Privacy-First Design
Developers control which sources they connect. The platform earns trust by respecting it.
A fair foundation for developer profiling
Where V1 landed.
Patterns found across multiple integrations generate scores defensible to both developers and recruiters.
Serverless architecture adapts to the complexity of all possible integrations without infrastructure tax.
Built as a self-assessment tool that happens to help with hiring. Not the other way around.
An ML + serverless stack built for integrations
React on the front, Node and ML on the back, AWS serverless underneath.
React
Frontend for the developer-facing dashboard. Designed for clarity in a category prone to dark patterns.
Node.js
Backend services for integrations, score calculation orchestration, and the API powering the UI.
Machine Learning
ML models trained on activity data from multiple integrations. Pattern detection at the core of the scoring engine.
AWS Serverless
Lambda, API Gateway, and the rest of the stack. Scales with each new integration without rewrites.
PostgreSQL
Developer profiles, integration tokens, and score history. Relational data for a domain that depends on traceable connections.
OAuth Integrations
Standard OAuth flows for connecting third-party developer platforms. Built once, applied to every new integration.
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