The Industry's First
Network-Powered
AI Engine.
Divide the payload. Aid the edge.
Not an AI monitoring tool. A distributed execution engine. We transform Cisco Catalyst 9300 Series Switches and CW917X Access Points into a sovereign, decentralized AI execution farm via native Docker containers. Leveraging asymmetric pipeline parallelism to execute high-density AI workloads with zero dedicated GPUs.
Absolute Data Sovereignty.
Consider a financial institution processing highly sensitive PII. Employees using public, external AI tools create massive Shadow AI compliance breaches. Divaid keeps the prompt entirely localized, giving teams the AI they want while keeping the inference swarm physically sandboxed within the branch.
The 1,000-Node Compute Matrix.
Deploying multi-million dollar GPU racks in every branch or campus is financially and energetically impossible. But scale changes everything. By harvesting dormant background cycles from the Catalyst Switches and Wi-Fi 7 Access Points already hanging from your ceilings, divaid.AI turns your existing network into an on-premise AI cluster with zero net-new power draw.
The Hidden Supercomputer: On-Premise vs. Cloud GPU
Aggregating just 100MB per AP yields over 100GB of working memory—surpassing the 80GB VRAM of a dedicated $15,000 NVIDIA A100 GPU.
Instead of renting expensive AWS instances, DDA awakens the massive, dormant multicore compute power already hanging from your ceilings.
APs run 24/7 via low-power PoE. We scavenge stranded background cycles, bypassing the massive multi-kilowatt (kW) footprint of cloud server racks.
Zero cloud API calls. By providing a secure, internal LLM, we effectively cure the enterprise Shadow AI problem while ensuring corporate IP never leaves the firewall.
Real-World Flow: Heavy Workload Orchestration.
Imagine processing a massive, confidential 500-page Financial Audit through an advanced LLM to detect compliance anomalies. Sending this to an external API violates banking sovereignty.
Instead, the prompt hits the Catalyst 9300 Orchestrator. The DivGraph Algorithm tokenizes the document and shatters the heavy attention-matrix calculation into 50 mini-tasks.
These micro-payloads are pushed instantly to 50 local CW917X Access Points running lightweight Docker workers. They execute their fraction of the neural network layer simultaneously. The returning tensors are instantly verified and recomposed by the C9300, delivering a comprehensive anomaly report locally, securely, and in seconds.
1. Heavy Ingestion
C9300 receives the 500-page Audit (PDF).
2. DivGraph Matrix Split
Algorithm divides the mathematical workload into 50 micro-tensor sequences.
3. Docker Swarm Distribution
Micro-tasks distributed via IOx to 50 AP nodes. Mini-inferences executed in parallel.
4. C9300 Verification & Recomposition
Orchestrator receives returning tensors, verifies hash integrity, and merges outputs.
5. Final Output Yield
Local Zero-Trust compliance report generated.
Cisco IOx & Native Docker Execution.
How does the fragmented workload execute inside individual nodes? Catalyst switches and modern edge APs possess robust ARM64 compute capacity. Cisco IOx allows native Docker containers to run directly on the hardware under strict cgroups. Here is how our three-phase pipeline makes it possible:
GGUF Encoding
We subject state-of-the-art dense transformer models to aggressive INT4 quantization. By dropping precision on the weight matrices, the payload is algorithmically compressed, fitting inside the Docker image without perplexity degradation.
The DivGraph™ Algorithm
Our proprietary DivGraph Distribution Algorithm resides in the C9300 Orchestrator container. When a heavy AI task hits the network, DivGraph shatters the underlying neural network layers into mini-tasks. Rather than passing parameter weights, it distributes fractional matrix multiplication tasks across the Docker nodes running on your AP swarm.
C9300 Merge
Once the AP nodes complete their fraction of the calculation, the tensors return to the C9300. The Orchestrator acts as the ultimate verifier, recombining the mini-tasks, decoding the hidden states, and returning the definitive final AI output with mathematical certainty.
Hardware-Level Isolation.
How do we run Generative AI across the network without impacting mission-critical connectivity? By leveraging Cisco IOx to enforce an airtight, hardware-level sandbox with absolute priority for line-rate traffic.
90% Dedicated to Wi-Fi 7
The vast majority of the AP's CPU, RAM, and NPU are completely untouched. Core network services have absolute priority at the hypervisor level.
10% divaid.AI Sandbox
We deploy the DDA Worker node via Docker cgroups. It is mathematically bounded to never exceed 100MB of RAM or interrupt network thread execution.
Micro-Orchestration on Catalyst.
The Catalyst 9300 Series switches act as the central brain. Instead of routing standard packets, our lightweight IOx app routes tensor states.
Untouched ASIC Performance
The UADP ASIC continues to switch enterprise traffic at line rate. divaid.AI does not interact with or degrade the data plane hardware switching.
Lightweight Master Node
A tiny fraction of the switch's application hosting CPU handles the DDA algorithm, keeping track of which AP is processing which neural layer.
Target Sectors for Sovereign AI.
Public cloud LLMs are commercially unviable for highly regulated industries due to data privacy laws. divaid.AI provides a secure, fully-managed alternative to unsanctioned public tools, eradicating the Shadow AI problem for sectors where data can never leave the building.
Government & Defense
Execution of intelligence models on classified data. The network itself becomes an air-gapped supercomputer, ensuring National Security compliance (ENS/FedRAMP) by default.
Healthcare & Hospitals
Real-time processing of patient telemetry, automated clinical transcription, and diagnostic RAG systems running locally on the hospital's Catalyst-backed VLAN. 100% HIPAA compliant.
Banking & Branches
Processing highly sensitive Personally Identifiable Information (PII) and internal audits. The branch network infrastructure executes the Generative AI tasks without relying on external corporate APIs.
Retail & Multi-Branch
Unlocking edge intelligence across hundreds of branch stores. In-store inventory computer vision, loss prevention, and customer foot-traffic telemetry processed entirely on local Wi-Fi 7 APs without consuming costly backhaul cloud bandwidth.
Smart Manufacturing
Ultra-low latency decision making for industrial automation. By moving inference directly to the physical APs covering factory floors and logistics hubs, round-trip cloud latency is eliminated entirely.
Energy & Utilities
Sovereign AI for power substations, water treatment facilities, and smart utility grids. Ensures strict operational continuity and anomaly detection in mission-critical environments disconnected from the public internet.
The Live Lab at Cisco Innovation Center BCN.
A turnkey, physical proof-of-concept environment deployed inside Cisco's flagship Innovation Center in Barcelona. Demonstrating live, air-gapped sovereign LLM inference distributed across enterprise switching and Wi-Fi 7 access points with zero cloud egress.
IOx Orchestrator Master with SSD-240G. Dynamic tensor sharding.
Distributed INT4 inference mesh suspended from timber roof trusses (<84MB/AP).
Screening Oncológico DICOM sin Nube
Caso de uso: 5.000 tomografías cerebrales en alta resolución. La legislación sanitaria y el secreto médico prohíben la salida de imágenes clínicas a APIs públicas externas.
Cómo lo demostramos: BioMistral 7B (4.8 GB) se fracciona en 32 capas entre los 12 APs (<84 MB RAM/AP). Ingesta y streaming en sala con 0 bps WAN y recibo criptográfico SHA-256.
Scoring AML SWIFT en Sucursal
Caso de uso: 50.000 operaciones SWIFT auditadas en tiempo real. Erradica la brecha de Shadow AI en banca procesando datos financieros y PII dentro de la propia entidad.
Cómo lo demostramos: Orquestación centralizada en el Catalyst 9300. Llama-3.1 8B corre aislado en microcontenedores IOx sobre la VLAN de la oficina sin servidores GPU ni nubes externas.
Prioridad Absoluta Wi-Fi 7 y QoS
Caso de uso: La exigencia ineludible de cualquier CTO o arquitecto de redes: garantizar que el tráfico corporativo, llamadas y videollamadas 4K tengan cero degradación.
Cómo lo demostramos: Inyección en vivo de un pico de tráfico saturando el AP-04. El scheduler Scavenger estrangula la IA a 0% de CPU en 3.8 ms migrando tensores con 0.0% de pérdida de paquetes.
Accelerating Cisco's 'Network for AI' Vision.
divaid.AI transforms the network from a mere transport layer into a distributed Secure AI Factory. By pioneering the Cisco Unified Edge for GenAI inference, we execute directly on Cisco's "AI-Ready Infrastructure" mandate, aligning perfectly with the core objectives of the Country Digitalization Acceleration (CDA) program.
Ideal for accelerating hardware refreshes in clients with obsolete infrastructure, pushing them toward Catalyst 9300 switches and CW917X APs. For clients who already own supported hardware, it provides a massive, immediate value-add.
Positions Cisco and its Partners as undisputed pioneers in a new category: Local AI Processing on Network Infrastructure. Currently, no other global vendor offers the capability to execute GenAI workloads natively across their switching and wireless fabric.
Provides a natural evolutionary path. As the client's GenAI demands grow, divaid.AI paves the way for future deployments of dedicated Cisco AI Pods, reinforcing their long-term strategy for secure, sovereign local AI.
Creates lucrative opportunities for the Cisco Partner Ecosystem. Drives profitable Professional Services (AI readiness audits, mesh deployments) and guarantees sticky, long-term Managed Service Provider (MSP) revenues.
AI on your Network.
Scale to the Pod.
Activate Sovereign AI on the Cisco Catalyst infrastructure you already own. By harvesting dormant compute cycles from your existing network, you prove the value of AI with zero upfront hardware investment. When your workloads scale, seamlessly upgrade to dedicated Cisco AI Pods.