Neurocad™ is the parametric design compiler for physical engineering. It turns static design artifacts — datasheets, PDFs, drawings, reference designs, and CAD outputs — into native, parametric, design-ready assets that work directly in the tools your teams already use.
It is not a CAD replacement. It is the intent layer that sits between unstructured engineering documentation and native CAD execution, eliminating the manual translation work that consumes a disproportionate share of engineering time.
No. Conventional conversion tools map formats converting bytecode, without reasoning about ‘intent,’ thereby losing constraints, relationships, and design-specific context in the process.
The information you need usually already exists. A datasheet contains the pin assignments, the package dimensions, the tolerances, and the thermal limits. The problem is that it is scattered across pages, leaving an engineer to read the entire document, hold it in their head, and relay it into the next tool by hand. That manual relay is where fidelity and time is lost. Neurocad does the reading in seconds and the relay losslessly.
Neurocad™ performs native synthesis. It extracts design intent from source documentation — resolving ambiguous or incomplete dimensions using ratiometric inference and manufacturing tolerances — then generates fully structured, parametric assets directly inside target tools. Parameters, constraints, and relationships are preserved, not approximated. This means the geometry holds under revision, the footprints don’t need to be redrawn, and the assembly behaves the way the original design intended.
The output is not a translated file. It is a design-ready asset that participates in validation, layout, and simulation workflows from the start.
No. Neurocad™ integrates with the tools your engineers are already proficient in, not as a replacement for them.
Your CAD environment stays intact. Neurocad™ is the intent layer between engineering content and those tools. It removes the manual reconstruction work that precedes CAD authoring, enabling clean, native outputs without requiring tool migration or additional licenses.
Most engineering automation tools optimize work inside a specific toolchain — better analysis within EDA, faster layout, cleaner collaboration within a cloud CAD environment. They assume the design is already structured when it arrives.
Neurocad™ addresses the layer before that: the conversion of static engineering artifacts — PDFs, datasheets, drawings, archived designs — into interactive, native, reusable assets. This is where most engineering time is actually lost, and it is the layer that established vendors have not addressed.
The clearest differentiator: Neurocad™ begins with real-world, unstructured engineering documents and produces native outputs for enterprise-grade tools. It does not require structured inputs, a specific tool, or a change to your existing environment.
They solve different parts of the same workflow. SnapMagic is a curated CAD library: a large, well-maintained collection of schematic symbols, footprints, and 3D models you search to find an existing part. It is excellent when the component you need is already in the catalog.
Neurocad™ starts where the catalog ends. Instead of looking up a model that already exists, Neurocad™ generates one from the source document. Hand it a datasheet, a package drawing, or a specification, and it produces a native, parametric, DRC-valid symbol, footprint, and 3D model directly in your tool, including for the parts no library covers: custom components, new releases, and anything you would otherwise build from a datasheet by hand. You review every extracted dimension before anything is committed.
If you have ever hit the point where the part you need is not in the library, that is the point Neurocad™ was built for.
SamacSys, also known as the Component Search Engine, is a curated library of free, verified symbols, footprints, and 3D models. When a part is not in the library, the SamacSys team will build it for you on request, which is a human build with a turnaround time. Neurocad™ generates the asset from the datasheet right in front of you, when you need it, Neurocad translates existing, new, custom and uncatalogued parts, with no wait and no manual rebuild. See how Neurocad™ is different from component libraries below.
Ultra Librarian is a PCB CAD library with over 16 million verified parts available free in many formats, and its 3D models are typically STEP files that carry shape but not parametric history. Like any library, its coverage is the size of its catalog, and its 3D models are typically delivered as STEP, which carries shape but not the parametric history that makes a model editable.
Neurocad™ generates from the datasheet rather than searching a catalog, and it produces true parametric models for SolidWorks, Fusion 360, and Inventor, not static STEP. It is also a vendor-agnostic tool funded by the engineers who use it, with no stake in which part you choose or which tool you design in. See how Neurocad™ is different from component libraries below.
Component libraries are lookup tools. You search a catalog of pre-built symbols, footprints, and 3D models and download the one you need. They are free, widely used, and genuinely useful when the part already exists in the catalog. Neurocad™ is synthesis, not lookup. It does not maintain a catalog. It reads the source document, a datasheet, drawing, or specification, resolves ambiguous or missing dimensions through ratiometric inference, and generates the asset on request through native synthesis. That difference changes what is possible in three ways.
Coverage. A library can only serve what has already been built, so its catalog is its ceiling. When a part is not there, the options are to wait for it to be built or to build it yourself by hand. Neurocad™ generates from any datasheet, which means it covers the custom parts, the newly released parts, and the long tail no library will carry, in the moment, from the source.
Scope. Most libraries serve the electronic side, and their 3D models are typically delivered as STEP, which carries geometry but not the construction history that makes a model editable. Neurocad™ generates true parametric models for SolidWorks, Fusion 360, and Inventor, so design intent survives the ECAD-to-MCAD handoff instead of arriving as a static solid.
Posture. Neurocad™ is a vendor-agnostic parametric design compiler, funded by the engineers who use it rather than by component sales or a CAD platform. It has no stake in which part you select or which tool you design in. The asset only has to be correct.
The two approaches work well together. A library is the fastest path to a part that already exists. Neurocad™ is the path to the part that does not, and the way to keep design intent intact across every tool boundary downstream. That is zero re-entry.
Neurocad™ is the parametric design compiler for physical engineering — the layer that sits between unstructured engineering artifacts and the tools your teams already use.
The problem is the same at every stage: the information exists, but the tools can’t read it. From the moment an artifact exists — a datasheet, a drawing, a reference design, a CAD output — Neurocad™ extracts the intent, and delivers native, parametric, design-ready assets directly into the tools that need them. No manual re-entry at any boundary.
That spans electrical and mechanical engineering workflows, systems engineers managing complexity across both, and OEM organizations where intent is routinely lost between programs and teams. It extends to semiconductor and component suppliers whose reference designs leave their hands as static PDFs with no visibility into what gets used, and distributors where engineers make high-intent component decisions with no native path from evaluation to design.
Neurocad™ addresses specific problems across several types of engineering organizations:
Electrical and electronics design engineers who spend time extracting data from datasheets, recreating footprints and symbols, and cleaning up broken ECAD imports.
Mechanical and CAD engineers who deal with broken ECAD-to-MCAD handoffs, non-parametric imported geometry, and models that don’t hold up under revision.
OEM engineering organizations operating across multiple CAD tools, geographies, and programs — where design intent is routinely lost during handoffs and reuse requires rebuilding from PDFs.
Semiconductor and component suppliers whose reference designs and application content are published as static files, losing attribution, design intent, and visibility once a customer downloads them.
Electronic component distributors whose product pages send engineers off-site during the highest-intent moment of evaluation.
Neurocad™ is built by engineers who spent their careers inside the workflows this platform is designed to fix. Previously at Accel EDA, Altium, Autodesk, Meta, Microsoft, HP, and Siemens, building tools used by millions of designers, engineers, and consumers worldwide.
Design intent is the reasoning behind a design decision — the constraints, relationships, and engineering judgment that made a choice valid. It is not the geometry. It is not the netlist. It is what those things mean and why they exist.
Why does it matter?
Because your tools don’t carry it. EDA and CAD tools in your stack are built to hold structured data. None were built to hold meaning. When a design crosses a tool boundary — datasheet to schematic, PCB to enclosure, simulation to CAD — the geometry moves. The reasoning doesn’t. What arrives on the other side is a representation. What stays behind is the intent.
The engineer on the receiving end rebuilds it manually. That is intent loss. At program scale, it compounds into something with a real cost: senior engineers pulled off forward design, review cycles that run longer than the underlying complexity warrants, mechanical models rebuilt from scratch because a STEP file carries shape but not constraints.
Neurocad™ captures design intent at the source — from datasheets, PDFs, images, reference designs, and existing CAD artifacts — and propagates it as native, parametric, DRC-valid assets directly into Altium, SolidWorks, and every tool downstream. No intermediate format. No manual reconstruction at any boundary.
A datasheet arrives as a verified, IPC-compliant schematic symbol, footprint, and 3D model, already in your tool, already parametric. A mechanical assembly survives an electrical update with its constraints intact. The decisions made upstream stay in the workflow.
That is zero re-entry. Design intent captured once, propagated everywhere.
Read more: The cost of losing design intent
This is the core insight behind Neurocad. A datasheet already contains the full design intent: pin assignments, package geometry, tolerances, electrical and thermal limits. None of it is missing. It is simply scattered across pages and formatted for a human to read, which means the only thing capable of assembling it and carrying it into the next tool has been an engineer, by hand, page by page. Neurocad reads the source the way the engineer would and relays a lossless version into every EDA and CAD tool downstream. The information was always there. Neurocad moves it without fidelity loss.
The reconciliation tax is what engineering organizations pay when design intent has to be manually reconstructed at every tool boundary across a program. Symbols and footprints recreated from datasheets that already contained that information. Parametric constraints rebuilt after a STEP handoff. BOMs reconciled by hand against a design that moved on without them.
Individually, each instance looks like small overhead. Across multiple engineers, multiple tool boundaries, and multiple revision cycles on a single program, the tax compounds. It shows up as review cycles that run longer than they should, senior engineers pulled off forward design to re-derive constraints already captured upstream, and NPI schedules that slip because data movement between tools requires human mediation at every boundary.
Intent loss is the root cause. The reconciliation tax is the accumulated cost. Zero re-entry eliminates it. Design intent is captured once and propagated into every target environment without manual reconstruction.
Read more: The cost of losing design intent
This is a core capability, not an edge case. Most real-world engineering documentation is incomplete.
Neurocad™ uses ratiometric inference to resolve ambiguous or missing dimensions — applying proportional reasoning and manufacturing tolerance standards before geometry is generated. This means the system produces accurate, manufacturable geometry even from imperfect source documents, rather than failing or propagating errors downstream.
Neurocad™ uses a combination of machine learning, reinforcement learning, and deterministic geometry generation. It is not a general-purpose language model applied to CAD.
The system is purpose-built for engineering workflows by a team previously at Accel EDA, Altium, Autodesk, Meta, Microsoft, HP, and Siemens — building tools used by millions of designers worldwide. The AI component handles intent extraction and inference from unstructured sources. The parametric modeling kernel then converts that structured intent into manufacturable geometry using deterministic, constraint-driven generation, not probabilistic output.
The result is consistent, verifiable, and revision-safe.
Before any asset is generated, Neurocad™ surfaces a structured model of how it interpreted the source material. Engineers can inspect this intent model — reviewing the parameters, dimensions, constraints, and relationships the system extracted — and refine it before generation begins.
This keeps design intent transparent and auditable. It also means the intent model becomes a reusable foundation for downstream tools, teams, and derivative designs.
Neurocad™ is designed to work with real-world engineering artifacts, not idealized inputs. It accepts:
If it exists in your engineering documentation environment, Neurocad™ is built to ingest it.
Neurocad™ generates native, production-ready design assets including:
Outputs are written directly into target ECAD and MCAD environments. No intermediate format, no post-processing, no manual cleanup.
Yes to 3D modeling and 2D design. Neurocad™ generates parametric 3D geometry from datasheets, drawings, and specifications, and supports 2D symbol and footprint creation for ECAD workflows. Simulation-ready assets — including geometry, constraints, and properties — are on the roadmap, built on the same kernel capabilities available in the platform today.
It handles complex geometry: B-Spline, Cubic Curve, Bezier, NURBS Curves, and NURBS Surfaces are all supported.
Outputs are written directly into the native format of the target CAD application via the local desktop service. Parameters, constraints, and feature history travel inside those native containers. Neutral formats are supported for import only, where they serve as one of many possible input sources.
DXF is treated as an input format, not an output format. Neurocad™ can ingest DXF files as source material for intent extraction. DXF does not carry parametric history — it encodes 2D geometry as flat drawing entities. When a DXF arrives as input, Neurocad™ extracts dimensional data from it and uses that as the basis for native synthesis. The output goes to the target CAD application in that tool’s native format, not back to DXF.
They do not carry them. STEP (ISO 10303) is a boundary representation format for geometric solids. It records the final shape of a body as faces, edges, and vertices with associated surface equations. It does not record the construction history that produced that shape — no sketches, no feature sequence, no constraint relationships, no design intent. There is no STEP feature for parametric intent.
A part exported from SolidWorks to STEP and re-imported arrives as a static solid: the engineer can measure it but cannot change its diameter by editing a parameter.
This is the fundamental reason Neurocad™ writes native assets into the target tool rather than relying on neutral interchange.
Read more: Why the mechanical model breaks after a board revision in PCB enclosure design
Feature history depends on a named, ordered construction sequence — sketch, extrude, fillet, mate — that is tool-specific and kernel-specific. In Fusion 360, geometry is computed from equations stored as B-Rep boundary representations; sketch entities do not have stable names at runtime, only handles allocated dynamically. This means querying or modifying a feature by name after the fact is unreliable. In SolidWorks, VBA-driven scripts that set feature parameters can produce syntax errors that prevent the model from loading at all, even when the geometry preview looked correct.
Neurocad™’s architecture addresses this with a script generator that produces a single parameterized construction script and compiles it into tool-specific output: SolidWorks VBA, Python for Fusion 360, JSON for KiCad. The goal is a result that loads and is editable, not just visually correct.
Neurocad™ is infrastructure-flexible. Collaboration, version control, and sharing are handled in the cloud. Data and assets can be accessed and opened in local tooling where required by your workflow, compliance requirements, or data governance policies.
It is designed to fit into existing engineering environments. Not to force a new infrastructure model onto your organization.
Yes. Neurocad™ supports git-triggered automation pipelines that scale from single-component validation to full library generation across teams and repositories. Pipelines can be configured to run on commit events, enabling continuous generation workflows that keep design assets in sync with documentation updates.
The manual process in electronics engineering workflows — extracting data from datasheets, rebuilding parametric constraints after ECAD-to-MCAD handoffs, reconciling BOMs by hand — is caused by a structural gap between unstructured engineering documentation and the CAD tools that need structured data. Most EDA tools operate inside that gap rather than closing it. Neurocad™ is built specifically to close it: extracting design intent from source documentation and delivering native, parametric assets directly into tools like Altium, Cadence, and SolidWorks without manual reconstruction at any boundary. That is zero re-entry. Not a feature inside an existing tool, but the infrastructure layer that removes the manual step entirely.
Read more: What works inside system engineering tools, what fails between them, and what fills the gap