Capabilities

LLM Solutions Architecture

  • Agent pipelines that are auditable, observable, and production-grade.
  • SOC 2 & FedRAMP-ready by design
  • LLM decision-tracking is built into the architecture
  • Delivered in <3 weeks for multiple enterprise teams

Semantic Search & Retrieval

  • Domain-tuned RAG built with OpenSearch and custom index logic
  • Sub-5s semantic search latency
  • 40% improvement in content traceability
  • Millions of docs indexed from native integrations with internal knowledge bases

Secure AI Infrastructure

  • Deploy safely — from GPU access to Kubernetes to inference endpoints
  • Terraform-based IaC with 100% environment parity
  • Multi-tenant, isolated architecture deployed in <5 days
  • CI/CD pipelines for fine-tuned models, prompts, and services

50

M+

Protected via AI-powered

fraud detection

4s (max)

End-to-end LLM

search latency

3-4 days

Saved per legal review through

explainable summaries

100%

IaC coverage with multi-cloud

deployment support

80%+

Latency reduction in production

LLM pipelines

99.7%


Inference accuracy maintained in production through continuous evaluation

About Infracta™

At Infracta™, we partner with high-stakes teams to architect explainable, production-grade AI systems — purpose-built for regulated industries, mission-critical operations, and enterprise-scale rollouts.

We specialize in operationalizing LLMs across compliance-heavy, high-security, and cost-sensitive environments, with a focus on measurable outcomes and sustained reliability.

Our impact to date:

  • 20M+ end users served across Fortune 100, federal, and healthcare platforms
  • $50M+ in risk reduction via AI-powered fraud detection and regulatory automation
  • 37% average infra cost savings through resource-aware optimization and autoscaling
  • 300+ engineers and policy teams trained on GenAI safety and governance frameworks
  • 99.9% uptime SLAs maintained across hybrid, multi-cloud, and air-gapped environments
  • 60% faster time-to-deploy, cutting delivery cycles from months to weeks
  • 70% audit prep time eliminated with token-level traceability and automatic logging
  • 80%+ latency reduction in live LLM pipelines using structured RAG and GPU-efficient serving
  • 40% improvement in knowledge retrieval precision, even on unstructured legacy corpora
  • 3-4 days saved per legal review using explainable summaries and citations
  • <5s average E2E query latency, even at scale, across distributed retrieval systems

Our technical focus includes:

  • FedRAMP-compliant AI infrastructure and IaC pipelines
  • Retrieval-augmented generation (RAG) with context-aware hybrid ranking
  • Secure fine-tuning, model versioning, and LLMOps automation
  • Observability-first GenAI stacks with built-in token-level audit trails
  • Native integration with enterprise knowledge bases and structured data lakes
  • Policy-aware access control, RBAC/ABAC enforcement, and model sandboxing


Whether you’re deploying into healthcare, finance, federal systems, or Fortune 500 stacks, we help your team build GenAI systems that are secure, auditable, and ready to scale — without compromising on trust or oversight.

Let’s build LLM systems that scale, stay compliant, and earn trust — without
compromise.

Start the conversation.