AI Assisted
Use AI to accelerate repetitive engineering analysis, triage, documentation and verification workflows.
AI-Accelerated Verification.
Accelerate repetitive and analysis-heavy verification work while keeping engineering review, validation and sign-off under human control.
AIV
AI Assisted
Human Validated
Secure
Where verification teams lose engineering time.
01
Test creation
02
Regression execution
03
Failure triage
04
Coverage analysis
05
Debug / root cause
06
Documentation
AIV targets repetitive, data-heavy and analysis-intensive portions of verification while leaving technical decisions and sign-off authority with the engineer.
Human Validated
Keep engineers accountable for decisions, sign-off and technical interpretation.
Secure
Design workflows around controlled access, approved data boundaries and deployment governance.
Measured
Track productivity, quality and closure outcomes rather than treating AI usage as the objective.
Where AIV can assist engineering teams.
01
Planning
Verification planning and test-intent analysis
02
Execution
Regression prioritization and repetitive analysis
03
Debug
Failure triage and debug-assistance workflows
04
Closure
Coverage and assertion analysis
05
Knowledge
Protocol, specification and engineering knowledge search
06
Documentation
Reusable testbench and verification documentation assistance
01
Engineering data
02
AIV assistance
03
Engineer review
04
Validation
05
Decision / sign-off
No autonomous sign-off. Engineering accountability remains with the responsible team.
Connect AIV workflows to verified engineering domains.
AIV is positioned as an assistance layer around verification workflows. Where AionSi has supporting technical evidence, visitors can move directly from the workflow to the underlying engineering reference.
01EVIDENCE READY
PCIe Gen6
Production-grade Data Link Layer engineering with link training, flow control, error recovery, power management and SoC integration.
View engineering evidence →02EVIDENCE READY
USB 3.x / USB4
Integrated USB controller engineering spanning PHY, link and protocol layers, power delivery, error recovery and host/device integration.
View engineering evidence →03EVIDENCE READY
DDR4 / DDR5
Memory-controller engineering covering command scheduling, PHY abstraction, refresh management, ECC/RAS, timing and SoC integration.
View engineering evidence →04EVIDENCE READY
HBM2e / HBM3
High-bandwidth memory controller engineering for AI, GPU and HPC systems with QoS-aware scheduling and thermal-aware integration.
View engineering evidence →05EVIDENCE READY
AMBA CHI / AXI
Coherent and non-coherent interconnect engineering for heterogeneous SoCs with QoS, configurable topology, monitoring and scalable agent counts.
View engineering evidence →06EVIDENCE READY
RISC-V
Processor-core engineering spanning embedded, edge-AI, performance and multi-core cluster tiers with formal and dynamic verification.
View engineering evidence →AI should accelerate engineering — not replace engineering accountability.
AIV is designed as an engineering-assistance layer. Teams define approved workflows, data boundaries, validation checkpoints and release criteria before using AI in production engineering processes.
On-premise deployment
Private / controlled cloud
Enterprise data boundaries
Start small. Prove value. Scale responsibly.
Select one workflow
Choose a bounded verification workflow with a clear owner and repeatable workload.
Baseline current effort
Capture the current engineering effort, turnaround and quality indicators.
Configure AIV
Define approved data boundaries, workflow rules, validation checkpoints and deployment controls.
Run a controlled pilot
Operate AIV alongside engineers without changing production sign-off authority.
Measure outcomes
Compare productivity, turnaround, quality signals and engineer acceptance against the baseline.
Review and scale
Expand only after the engineering team validates the workflow and results.
Measure the engineering outcome — not the AI usage.
Start with an agreed baseline and evaluate the workflow against measurable engineering signals.
01
Engineering hours recovered
02
Failure-triage effort
03
Debug turnaround
04
Coverage-analysis effort
05
Documentation effort
06
Engineer validation / acceptance
AI that strengthens verification engineering.
AIV sits inside AionSi's broader engineering model across design verification, protocol verification, UVM, coverage, assertions and regression workflows.
Bring one verification workflow. We will map the acceleration opportunity.
Share the workflow, current bottleneck, data boundary and expected outcome. AionSi will map a controlled AIV discovery path.