AuricStack Solutions is a newly established technology company backed by experienced professionals with 10+ years of experience across AI, cloud, software engineering and digital products.
We build practical software solutions—from AI prototypes and modern web applications to cloud and enterprise platforms.
AuricStack may be new, but the engineering experience behind it isn't.
AWS/Azure infrastructure provisioning with Terraform and enterprise release management.
AWS architecture and optimization work involving ECS, load balancing, CloudFront, WAF and cost tracking.
LangChain-based AI agents supporting seminar creation, review management and payment-confirmation workflows.
iOS video calling using WebRTC, Ant Media Server, CallKit and VoIP push notifications.
The examples above represent professional experience contributed by our team members during previous engagements. They are presented to demonstrate team capability and are not represented as projects completed by AuricStack Solutions.
Working AI prototypes we've developed, plus illustrative concepts showing how we'd approach similar problems.
An AI-powered system that finds relevant seminars, events and meetings from Gmail, WhatsApp groups and LinkedIn, extracts key information, registers where applicable, tracks opportunities and sends timely reminders.
An AI-powered trading platform that analyzes activity across multiple broker accounts, detects emotional patterns, measures trading discipline and risk, and provides AI-driven decision support to help traders avoid emotionally driven trades.
A concept for centralizing patient records, appointments and communication in one platform.
A concept for real-time bus tracking and pickup alerts that keep parents informed.
Start with a focused prototype, validate the workflow, and scale it into a production-ready solution.
Understand the business problem and define a practical roadmap and architecture.
Build a focused working prototype and validate the workflow with real inputs.
Expand the validated prototype into a usable first release.
Deploy with Infrastructure as Code and CI/CD, then scale with ongoing support.
Start focused and validate capability and team fit.
Choose the engagement model that fits the scope.
Continue with enhancements, maintenance and optimization after launch.
AI · ML · IoT · Cloud · Web & Mobile · UI/UX · Digital Solutions