Kinetic Edge Labs • Senior Web Engineering

Engineering at the Edge of Technology

We build great high-performance applications leveraging an expanded full-stack ecosystem across Frontend Mastery, Backend & APIs, AI & Data Intelligence, and Cloud Infrastructure. Always going the extra mile to deliver best-in-class solutions for our clients.

Angular TypeScript NestJS GraphQL AI & LLMs Cloud & DevOps
Kinetic Edge Labs Expanded Technology Ecosystem Infographic

Ready to make an impact?

Let's move fast, iterate daily, and solve real problems.

LET'S BUILD IT TOGETHER
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FEATURED PROJECTS

Contract Analytics 2.0

Flagship Solution • Kinetic Edge Labs

Project Mission

"At Kinetic Edge Labs, our mission for Contract Analytics 2.0 is to engineer a cutting-edge Data-first CLM platform that automates risk identification, clause extraction, and obligation tracking for enterprise legal teams using Angular, NestJS, and AI."

AI Extraction

Automatically find key dates, values, and clauses in complex documents.

Risk Mitigation

Identify regulatory risks and outdated sections in real-time.

Performance

Track renewal timelines and obligations across thousands of files.

Total Visibility

Create a searchable 'Single Source of Truth' for all contract data.

Frontend Mastery

Angular (Reactive Components)

Backend Power

Nest.js (Modular Architecture)

Architectural Pipeline: AI-Powered
Contract Lifecycle Management (CLM)

FRONTEND
STAGE 1 - SECURE DATA INTAKE
Contract Form
➔

Angular Frontend & NestJS Validation

Dynamic schema-driven forms collect metadata before routing through NestJS for rule-based validation.

Secure Supabase Bucket Storage

Uploaded contracts are stored in private, secure buckets with strict data residency policies.

supabase
BACKEND
STAGE 2 - LOCAL AI DIGEST & PROCESSING
TTildeOpen
✢Embedić

Local AI Models (TildeOpen & Embedić)

Offline processing uses TildeOpen for language morphology and Embedić for Serbian semantic mapping.

Text Chunking & Normalization

Systems decompose contracts into searchable segments and normalize text for script-agnostic searching.

DATABASE
STAGE 3 - PERSISTENT SEMANTIC STORAGE
PostgreSQL
Metadata in PostgreSQL

Relational data and audit trails are managed with strict Postgres field constraints.

pgvector
Vectorized Search with pgvector
<3ms
Under 3ms Semantic Retrieval

Optimized RLS policies and pgvector embeddings enable high-speed semantic retrieval.