Blog
Insights, news, and best practices from AstraQ
Post-Quantum Cryptography: Lattice-Based Cryptography and Mathematical Foundations
A comprehensive deep-dive into lattice-based cryptography, the mathematical backbone of post-quantum security. Explore the geometry of lattices, the Learning With Errors problem, and how ML-KEM and ML-DSA achieve quantum resistance.
Trajectory Reconstruction: Interpolation
Our Interpolation engine reconstructs vessel trajectories during AIS data gaps using physics-based cubic spline interpolation, quadratic speed modeling, and smooth angular transitions to create continuous, realistic paths.
Correlation Engine: Matching Detections to Vessel Identities
A deep technical dive into the Correlation Engine of OS², exploring the mathematics of weighted bipartite matching, the physics of kinematic coherence, and the algorithmic elegance of the Hungarian method in fusing anonymous satellite detections with AIS identity data.
Vessel Detection
An exhaustive technical exploration of the dual-sensor vessel detection architecture within OS², dissecting the physics of Synthetic Aperture Radar (SAR) and Electro-Optical (EO) imagery, the implementation of Vision and Swin Transformers, and the mathematical rigor of multi-scale feature pyramids.
Maritime Domain Awareness System: Technical Overview
Discover how AstraQ's OS² Maritime Domain Awareness system transforms fragmented satellite imagery and vessel tracking data into coherent, actionable intelligence through automated detection, intelligent correlation, and predictive analysis.
Post-Quantum Cryptography: The Quantum Threat and Cryptographic Foundations
A comprehensive deep-dive into the mathematical foundations of post-quantum cryptography. Understand Shor's algorithm, Grover's algorithm, and why current cryptographic systems are vulnerable to quantum attacks.
AstraQ Cyber Defence Shortlisted Among Top 6 Teams for AI Grand Challenge at IIT Delhi
AstraQ Cyber Defence selected among top 6 finalists for the NCIIPC Startup India AI Grand Challenge for their advanced Retrieval Augmented Generation (RAG) system.
LangChain 1.0: An Introduction
An introduction to LangChain 1.0, featuring real-world code examples for building production-ready AI agents.
Control Plane Resilience: Handling Cascading Failures in Distributed Orchestration
Building fault-tolerant control planes with circuit breakers, graceful degradation, and bulkheads to prevent cascading failures in distributed workload orchestration systems.
Enterprise Audit Logging and Monitoring: The Missing Piece of the Control Plane
Implementing tamper-proof audit logging and real-time monitoring for ephemeral workloads using Go middleware, ClickHouse, and the Decorator pattern.
Zero-Trust Networking for AI Agents: Protecting Your Internal VPC
Preventing SSRF and lateral movement by dynamically provisioning Kubernetes Network Policies for untrusted workloads.
Hardening the Control Plane: From Pods to MicroVMs
Securing your workload orchestrator by swapping standard Containers for Firecracker MicroVMs using Kata Containers and the Go WorkloadRuntime interface.
Building a Polymorphic Workload Orchestrator with Go and Kubernetes
Learn how to build a scalable control plane for on-demand AI agents and data tasks using Go interfaces, Redis queues, and Kubernetes.
Guardrails for RAG: Preventing Hallucinations and Ensuring Factual Accuracy
A comprehensive guide to preventing hallucinations in RAG systems. Learn self-consistency checks, retrieval grounding verification, citation enforcement, and production-ready guardrail patterns.
Scaling RAG Systems: Caching, Sharding, and Performance Optimization
A comprehensive guide to scaling RAG systems for enterprise workloads. Learn caching strategies, collection sharding, replication patterns, and performance optimization techniques to handle millions of queries.
Building Multi-Tenant RAG Systems: Isolation and Resource Management
A comprehensive guide to implementing tenant isolation, resource quotas, and data privacy in multi-tenant RAG systems. Learn production-ready patterns for secure and scalable AI applications.
Evaluating RAG Systems with RAGAS: Metrics That Matter
A comprehensive guide to evaluating RAG systems using RAGAS framework. Learn how to measure faithfulness, answer relevancy, context precision, and context recall to build reliable AI applications.
Building Multi-Hop RAG Agents with Chain-of-Thought Reasoning
Learn how to build advanced RAG agents that can perform multi-hop reasoning, query restructuring, and use retrieval as a tool with LangChain, chain-of-thought, and multi-shot prompting.
Building Production-Ready RAG Systems: A Complete Guide
A comprehensive guide to Retrieval-Augmented Generation (RAG) systems using Python, Qdrant, and FastEmbed with hybrid search combining dense, sparse, and late interaction embeddings.
AstraQ Cyber Defence Wins Grant for Innovative Phishing Detection Solution at IMC 2025
AstraQ Cyber Defence recognized for innovative AI-driven phishing detection at Indian Mobile Congress 2025.
The Rising Threat of Phishing: One Click Can Cost You Everything
An in-depth look at modern phishing tactics, the role of AI in cybercrime, and how to defend against evolving digital threats.