A unique Agent Harness with in-house learning loops powering Visual Agentic Chip Design.
The architecture in one diagram. No data leaves your boundary.
Browser-based UI on top. Your infrastructure in the middle. Your HPC and LLM endpoints on the edge. Every byte of design data stays inside the perimeter you already control.
01
Browser-based UI
Runs on any laptop with a browser. No install, no per-user provisioning.
02
Server on-prem
Backend deploys into your VPC, data center, or fully air-gapped.
03
HPC-ready
Dispatches synthesis, simulation, place & route, DRC/LVS to your cluster.
We build your chip design agent harness for your unique environment.
01
Real-world task focused
Trained and evaluated on real chip design tasks — not synthetic benchmarks.
02
In-house data generation
Task data is generated in in-house learning loops with customers. Customers own it at the end.
03
Flow-aware, not IDE-bound
Understands EDA toolchains, not just HDL syntax.
04
Longevity of in-house data
Modernizes and brings back to life legacy IP — port nodes, refactor interfaces, lift CDC issues.
05
Visual intelligence
Multimodal spatial reasoning over block diagrams, FSMs, waveforms and RTL structures.
06
No hyperscaler dependency
Tool-agnostic, LLM-agnostic. Runs wherever you need it — Azure, AWS, or your own VPC.
Where the intelligence comes from.
Chip-Trajectory Datasets
Thousands of hours of proprietary, multimodal agent-debugging trajectories feed a continuous self-learning loop. This is how Chipmind learns to navigate EDA toolchains, interpret logs and waveforms, and reason about design flows — before ever touching your data.
![Diagram showing apb_bus connecting to timer_1 module with signals pcl, tim_irq, and load[31:0] and a chat interface.](https://cdn.prod.website-files.com/6a0c94bb7898479170a88017/6a4adde2fc42f4d1ca5b7c71_continous-learning-2-2.png)
Context Engineering
Chipmind ingests your complete design files, hierarchies, and constraints into a unified Chipgraph. Custom ACE (Adaptive Context Engine) dynamically retrieves the most relevant context from the Chipgraph for each task through iterative refinement — no fine-tuning required.
Value of in-house training data
Agents directly execute EDA tools, analyze logs and waveforms, and learn from results. The longer Chipmind works with your flow, the better it gets at your specific design patterns.
All processing happens on-prem or in your VPC. Chipmind never stores design data beyond the active task.
Every Chipmind Agent runs inside a contained, ephemeral execution environment.
Your environment, your tools.
Chipmind connects to your existing VCS, EDA tools, and HPC cluster. On-prem, VPC, or cloud. Your choice.
Drop a task in plain English.
Open a GitHub issue, type an @mention, or use the Chipmind GUI. No new syntax and no scripts. Just describe what you need.
Agents plan and run it autonomously.
The agent reads your design context, plans the task, runs your EDA tools, and iterates until the result is correct.
PR ready. Audit trail included.
Results come back as a reviewable PR with full execution log. You stay in control and your agents handle the work.
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FAQ
Chipmind deploys, maintains, and trains optimized AI models securely within the client's own environment. Your highly sensitive RTL codebases, documentation, and internal telemetry never leave your secure infrastructure.
Chipmind utilizes self-adapting mechanisms that read local scripts, automation tools, and legacy setups, calibrating the agent workflows to match your engineering team's exact methodologies.
The SMRE is the proprietary core engine that drives the user experience. It automatically predicts and generates the optimal visual format for a task—like instantly projecting structural schematics for wiring or digital waveforms for timing bugs.
By running in-house learning loops, the agent harness safely records expert engineering telemetry and datasets locally. This automatically secures vital institutional design knowledge so it remains continuously reusable by the team.
Chipmind achieves practical determinism by anchoring its agent generation pathways to absolute hardware realities and strict verification constraints. While the AI remains flexible enough to sketch unwritten architectures, this underlying technical framework guarantees it never hallucinates faulty logic, ensuring consistent, reproducible results.
Unlike generic LLMs that treat code purely as text, Chipmind understands structural hierarchy, logical constraints, and hardware description languages (HDL) to execute complex, multi-hop architectural reasoning.
Ready to see Chipmind in action? Book a Call.
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Let AI do the chips.