RESEARCH PROGRAMS // DIRECTORY

Core Research Disciplines

Swadeshi AI approaches computing as a continuous spectrum: from autonomous software agents reasoning over formal specifications, to defensive cybersecurity boundary verification, to physical analog silicon architectures.

TRACK // 01 Active

Agentic AI & Autonomous Loops

Constructing deterministic multi-step planning runtimes, structured reasoning loops, and verifiable tool-calling harnesses.

Methodology Observation-action cycle, AST diff validation
Applications AI-assisted engineering, automated code analysis
TRACK // 02 Active

Cybersecurity & Defensive Systems

Telemetry-driven attack surface modeling, protocol fuzzing, identity containment, and authorized defensive testing frameworks.

Core Ethos Defensive security, authorized testing, disclosure
Scope AI system vulnerability lifecycle & supply chain
TRACK // 03 Active

AI Systems & Context Engineering

High-throughput inference orchestration, KV-cache tiering, structured JSON streaming, and deterministic reliability benchmarks.

Systems Distributed agents, memory caches, RPC mesh
Target Sub-10ms tool turnaround, zero drift
TRACK // 04 Active

Model Context Protocol (MCP)

Standardized bidirectional client-server interfaces decoupling reasoning models from physical environments and local tools.

Protocol MCP v1.0 specifications & adapters
Safety Capability tokens, runtime sandboxing
TRACK // 05 R&D Direction

Analog Computing

Simulating non-clocked, continuous-time differential operations to overcome the von Neumann memory-compute bottleneck.

Approach Continuous physics conduction, low-energy math
Stage Circuit simulation & mathematical models
TRACK // 06 R&D Direction

Semiconductor Lab

Long-horizon exploratory studies in transistor layout, mixed-signal design, and custom analog accelerators for machine intelligence.

Integrity Truthful R&D — no fabricated silicon
Tools SPICE, open-source EDA, physical simulation

RESEARCH ARCHIVE

Formal Publications & Technical Notes

Pre-prints, system specifications, and reproducible benchmark repositories are being compiled. All publications from Swadeshi AI Private Limited undergo rigorous internal verification before public release.

[NO FABRICATED CITATIONS // OPEN SCIENCE PROTOCOL ACTIVE]