Intics Edge AI

Absolute data sovereignty.
Deterministic local compute.

Edge AI executes models locally — on enterprise PCs, workstations, field gateways, and micro-servers — instead of inside centralized, multi-tenant clouds. Moving compute to the data source eliminates network latency, bandwidth overhead, and cloud dependency, and gives regulated sectors a zero-trust perimeter where confidential data, proprietary blueprints, and sensitive records are processed and tokenized entirely within the local ecosystem.

Scalable Silicon-Native Compute
From ultra-efficient 8-core mobility to 32+ core edge power

Turn local endpoints into dedicated token factories. Integrated System-on-Chip (SoC) architectures execute heavy multi-threaded enterprise workloads locally.

Mission-Critical Field Intelligence
100% operational autonomy, even completely offline

Process complex engineering schematics at remote project sites, or secure protected health information (PHI) within private hospital networks.

8–32+
Core architectures
50
NPU TOPS
4×
NPU power efficiency
100%
Offline capable
The Case for Edge

Enterprise intelligence under a single, local roof

Document intelligence in security-sensitive domains like Engineering, Procurement & Construction (EPC) and Health Insurance demands uncompromised speed, ironclad security, and structural data control. Cloud-based AI exposes organizations to unpredictable subscription overhead, variable network latency, and multi-tenant compliance risk. Intics Edge AI removes the reliance on remote cloud endpoints — embedding our Agentic Document Intelligence (ADI) directly onto local client and workstation hardware, so active workflows and vector knowledge bases operate entirely on-site.

Silicon-Native Optimization

The System-on-Chip advantage

The Intics stack is optimized to exploit the hardware-level innovations of Intel® Core™ Ultra processors — offloading heavy deep-learning inference away from the main processing loops and distributing workloads across specialized SoC tiles and scalable core configurations to match your exact deployment footprint.

Lunar Lake
8-core efficiency

Built for mobile field operations. An ultra-low-power island architecture handles localized data ingestion, field forms, and on-site lookups smoothly on lightweight laptops and tablets — without draining battery life.

Panther Lake
16-core mobility

Built for high-throughput mobile applications. A built-in NPU 5 architecture outputs up to 50 NPU TOPS for concurrent multi-agent document verification and immediate context extraction for claims adjusters and regional offices.

Nova Lake
32+ core enterprise scale

Built for desktop workstations and localized edge micro-servers. High-density multi-threaded performance (scaling to a 52-core dual-compute tile design) plus a Big Last Level Cache (bLLC) make each endpoint a local Document Token Factory, converting thousands of pages per second without network lag.

Dynamic Load Balancing

Balanced across the hardware layer

Instead of hitting processing walls, Intics works with native instruction sets and optimization toolkits to balance execution across the silicon.

Neural Processing Unit (NPU)

Dedicated to sustained matrix multiplications — executing token parsing and entity extraction locally, with up to 4× better power efficiency than traditional processing methods.

Heterogeneous distribution

Light text manipulation runs on the CPU, spatial and graphical document elements route through the integrated GPU, and long-form document vectors run continuously on the NPU.

On-chip security

Raw documents are tokenized directly in system memory — shielding sensitive intellectual property and client files from ever crossing an external internet gateway.

Targeted Applications

Built for regulated, document-heavy work

Health Insurance
Zero-trust claims & policy auditing

Flawless HIPAA & PHI compliance. Processing occurs entirely in-memory on local Intel Core Ultra hardware, so personally identifiable information never touches an external cloud provider — neutralizing data-breach vectors.

Accelerated claims auditing. Localized agentic workflows compare incoming multi-page medical claims against policy rules at the desk level, shortening processing from days to seconds while eliminating external cloud API costs.

EPC
High-performance autonomy in the field

Disconnected, offline operations. Construction sites are frequently remote. Engineers query localized project knowledge bases, extract structural specifications, and audit vendor-compliance files completely offline.

Blueprint asset extraction. High-core-count edge workstations parse complex engineering diagrams locally, flag data omissions, and cross-reference material spec sheets at the field office — before structural issues manifest on-site.

Cloud AI vs Intics Edge AI

The architectural difference

Traditional Cloud AI

Data security: multi-tenant cloud risk; payload leaves the perimeter

Network: requires a constant broadband connection

Scalability: rigid, costly virtual instances

Latency: variable, dependent on network congestion

Acceleration: generic cloud allocations

Intics Edge AI

Data security: 100% sovereignty; files stay inside local SoC memory

Network: zero dependency; full offline operational capacity

Scalability: scales across 8, 16, and 32+ core architectures

Latency: deterministic, sub-millisecond local processing

Acceleration: native offloading to dedicated NPU engines

Collapse the gap between execution and knowledge

True operational velocity means coupling active automated workflows with localized knowledge caching on high-efficiency Intel Core Ultra System-on-Chips — an uncompromised, hyper-fast document-intelligence environment that never leaves your perimeter.