contact@frostlabs.io
42 Mamnoun Streek, LAC2
Mon - Sat: 10.00 - 18.00
Frost AI Fabric isn’t a SaaS product wrapped around a model — it’s a modular infrastructure layer designed to integrate deeply into your existing environment. Every component of our platform has been engineered with enterprise-grade requirements in mind:
Security-First Architecture – Built with zero-trust principles, encryption, and RBAC from the ground up.
Composable & Modular – Deploy only what you need, and evolve over time
Observable by Design – Metrics, logs, traces, and audits baked into every layer.
AI-Native Core – Optimized for agentic workflows, retrieval-augmented generation (RAG), and autonomous reasoning.
Sovereignty Ready – On-premise, cloud, or hybrid deployment with jurisdictional control.
The core of Frost AI Fabric is built around five guiding principles that make it uniquely suited to enterprise intelligence workloads:
Data Proximity – AI should run where your data lives. Frost integrates directly into your existing data platforms (e.g., Snowflake, object storage, on-prem data lakes) to eliminate latency, reduce egress costs, and improve governance.
Composable Intelligence – Each module is independent but interoperable, letting you build intelligence like LEGO blocks.
Separation of Concerns – Ingestion, retrieval, inference, and interaction are cleanly decoupled — ensuring scalability and resilience.
Observability Everywhere – Every component emits metrics, logs, and traces — making AI pipelines as transparent as traditional apps.
Secure by Default – Encryption, IAM, and auditability are not afterthoughts — they are the foundation.
Frost AI Fabric is structured into five primary layers, each responsible for a critical part of the intelligence lifecycle:
Continuous ingestion from APIs, databases, file systems, streaming platforms, and web sources.
Built-in connectors for YouTube, RSS, SharePoint, S3, GCS, and more.
On-the-fly enrichment, cleaning, and metadata tagging.
Semantic indexing and retrieval across unstructured data.
Hybrid vector + keyword search for precision and recall.
Built-in support for embeddings, reranking, and metadata filtering.
Agentic orchestration connecting LLMs, APIs, and business logic.
RAG pipelines, function calling, and decision-making workflows.
Multi-model compatibility (OpenAI, Groq, Llama, Mistral, etc.).
Unified interface layer with chat, search, and dashboard capabilities.
User access control, memory, and context persistence.
Ready-to-integrate UI components for enterprise portals and apps.
Unstructured data storage on internal stages, with governance and lifecycle policies.
Native integration with data platforms like Snowflake, Delta Lake, and S3.
Fine-grained access control, lineage tracking, and auditability.
Security is not a feature — it’s a non-negotiable foundation. Frost AI Fabric is built to meet the most demanding enterprise and regulatory requirements:
End-to-End Encryption: TLS in transit, AES-256 at rest.
Role-Based Access Control: Fine-grained IAM integrated with enterprise SSO (SAML, OAuth, SCIM).
Auditability: Full traceability of data access, inference decisions, and pipeline actions.
Compliance-Ready: Designed with SOC 2, ISO 27001, HIPAA, and GDPR alignment in mind.
Policy Enforcement: Data retention, masking, and governance policies built in.
In regulated industries and sensitive jurisdictions, control over data and models is paramount. Frost AI Fabric is designed to operate in sovereign environments:
On-Prem Deployment: Run the entire stack within your own data center or private cloud.
Jurisdictional Isolation: Ensure that data never leaves specific geographic or legal boundaries.
Custom Model Hosting: Bring your own models or use local inference providers (e.g., Groq, Hugging Face, or private Llama endpoints).
Air-Gapped Deployments:* Full functionality without external internet connectivity.
Enterprise AI workloads demand predictable performance and operational visibility. Frost AI Fabric is engineered for both:
Elastic Scaling: Auto-scale ingestion, indexing, and inference workloads based on demand.
Cost Efficiency: Compute resources optimized for workload profiles and dynamic scaling.
Observability: Metrics, logs, traces, and alerts for every component, exposed via Prometheus, Grafana, and OpenTelemetry.
Performance Benchmarks: Built-in profiling tools to measure retrieval latency, inference speed, and throughput.
Frost AI Fabric is deployment-agnostic, giving enterprises complete flexibility:
Cloud-Native: Deploy on public cloud infrastructure (AWS, Azure, GCP) with autoscaling and managed services.
On-Premises: Run on virtualized infrastructure, bare metal, or Kubernetes clusters.
Hybrid: Mix on-prem and cloud components for data locality and compute elasticity.
Embedded: Deploy modules as microservices within existing enterprise apps..
The future of AI isn’t just about LLMs — it’s about **autonomous, goal-driven agents** operating across your enterprise. Frost AI Fabric is built for that future:
Agent runtime orchestration with task scheduling, memory, and planning.
Continuous learning and adaptation loops.
Inter-agent communication and collaboration support.
Enterprise control plane for agent governance, security, and auditability.
