Apex ships one product. Aether is the foundation model — trained end-to-end on simulation, instrument data and design history. It ships into engineering, semiconductors, drug discovery, autonomous labs and software on the same weights, the same runtime, the same safety story — applied to the workloads that actually matter.
Aether is trained on simulation rather than text. The same weights handle CFD, FEA, electromagnetics, quantum chemistry, biology and digital silicon — under one set of contracts.
Engineering, semiconductors, drug discovery, autonomous labs, software. Each has dedicated agents, validated benchmarks and a documented pilot pattern.
Long-horizon agents, deterministic memory, capability-gated tool use, eval-gated deploys. The substrate every Apex discipline runs on.
Managed cloud, customer VPC, on-prem, or air-gapped. Same runtime, your choice of boundary.
Fixes a class of drift artefacts on rollouts longer than 4,000 time-steps for high-Reynolds external aerodynamics.
First general-availability release. Three sizes, 1M-token context, streaming rollouts, full model card published.
Adapter total: 15. Memory and review history now shared across all surfaces.
First-class drivers. Plate logistics planner now respects reagent-lot lineage when allocating across instruments.
Everything else in the family runs on Aether. One foundation model trained on simulation trajectories, instrument data and design history — not on scraped text. Three sizes, 1M-token context, full model card.
Aether is trained on simulation, not scraped text. It runs forward in time across domains the same way reality does — coupling CFD, FEA, EM, quantum chemistry, biology and digital silicon under one set of weights. Everything else at Apex is built on it.
Each discipline ships with its own agents, benchmarks, deployment templates and pilot patterns. The model underneath is the same.
The capability under every other one. Aether builds a forward-rollable, multiphysics twin from the CAD, sensors and docs you already have, keeps it synced by data assimilation, and runs the what-ifs you would never risk on the asset.
Specify the loads, constraints and objectives, and Aether generates optimized geometry and forward-rolls the physics on every candidate — topology optimization, generative lattices and material-and-process co-design, manufacturing-aware and validated, not just generated.
SAST, SCA, DAST, IAST, RASP, secret scanning, IaC, API security, supply chain and ASPM under one model — replacing open-source vulnerability scanning, application-security testing suites, static-analysis suites, runtime application security and SCM-native security, with an agentic copilot, sub-5-minute PR scans and false positives under ten percent.
Extended detection and response across endpoint, identity, email and cloud, fused into one incident — with automated attack disruption and a Security Copilot. full XDR parity, replacing endpoint EDR platforms, autonomous endpoint platforms and XDR suites plus your SIEM and SOAR, self-hosted and air-gapped.
Image and IaC scanning, admission control, eBPF runtime detection and automated enforcement, with KSPM posture and network microsegmentation — container security suites/runtime security platforms/agentless cloud posture parity on one model, self-hosted and air-gapped.
Multi-source collection, a threat graph, malware analysis, actor tracking and finished intelligence — ingesting at 100,000 indicators/s and pushing to your controls in under 60s. threat-intel parity, on a platform you run, self-hosted and air-gapped.
Passive-first asset discovery, OT protocol DPI, behaviour anomaly and ICS threat detection, attack-path analysis and segmentation simulation — OT-security parity on one model, coupled to the physics to rank alerts by consequence, self-hosted and air-gapped.
ML classification, DSPM, access governance, activity monitoring and DLP enforcement on one model, with ransomware and insider-threat detection — data-security parity, ≥95% classification and sub-200ms enforcement, self-hosted and air-gapped.
ZTNA, secure web gateway, CASB, firewall-as-a-service and inline DLP on one policy engine, with a continuous trust engine — SASE parity, inline under 50ms, and uniquely self-hosted and air-gapped.
Aether is what an engineering office looks like when the model is the substrate. CFD, FEA, electromagnetics, multiphysics, acoustics, thermal, fatigue, additive — unlimited workloads across every engineering discipline, in one project file.
The incumbent commercial CAE suite that ships your simulation, signoff and optimisation tools under separate seven-figure renewals.
Pick one programme — a wing-body study, a battery-pack thermal envelope, an antenna ground plane. Run Aether for engineering alongside the incumbent for a quarter; we co-author the comparison.
Specialist agents drive a complete chip flow: 3DIC architecture, RTL, physical implementation, IP integration, verification, multiphysics signoff, manufacturing, silicon lifecycle. Ships with a comprehensive silicon-IP catalog.
The incumbent commercial EDA suite — synthesis, P&R, timing, power, EM/IR and functional verification under separate licenses.
Bring one block of an in-flight design. We re-implement it on Aether for semiconductors, deliver matched signoff, and you keep the database.
Specialist agents for the path from target to lead: docking, FEP, MD, QM/DFT, ADMET, pKa, pharmacophore, ligand prep, generative chemistry, biologics design, materials discovery. Each agent is independently deployable with stable REST/gRPC contracts.
The computational-chemistry suite, the docking/FEP toolchain, the molecular-dynamics package and the in-house ADMET pipeline.
Pick a target you've been working on. We re-rank your existing hits and propose ten new ones — with our reasoning and predicted ADMET. You decide what to test.
Active-learning campaigns, ADMET endpoints, assay scheduling, chain-of-custody and biosecurity guardrails — running on real instruments. SiLA-2 gRPC for liquid handlers and dispensers; protocol export for open-source robotics; ALCOA+ and 21 CFR Part 11 audit out of the box.
Vendor lab schedulers, scientific-data-lake platforms and the bespoke wet-lab orchestration you've maintained internally.
Run one active-learning campaign on your existing instruments. Two weeks of integration, four weeks of campaign, one report.
Real-time collaboration, performance profiling, cross-language migration, CVE-aware review. Fifteen adapters across the major IDE surfaces and coding-agent runtimes let Aether meet your engineers wherever they write code.
The editor-embedded coding assistant, the long-horizon coding agent and the pull-request automation you currently pay for separately.
Pick one team and one repo. We deploy the SWE adapter, mirror your review policy, and report metrics after thirty days.
Contact dynamics, domain randomization, synthetic perception, imitation and policy training under one world model — with a calibrated reality gap and an honest fidelity tier on every rollout. The simulator the embodied-AI labs train and transfer through.
Vulnerability research, CVE-aware review, incident response, threat intelligence and adversary emulation under one model — plus a digital twin that tests defenses against a sandboxed copy of your estate. Built so the same capabilities cannot be turned offensive.
OT and critical-infrastructure security on the one model that already simulates the physics. Asset and protocol mapping, IT/OT boundary analysis, consequence simulation and ICS adversary emulation — safety-first, and built never to touch a live process.
“We expected an AI that would write Python around our existing tools. We got something that replaces them. The renewal we were dreading is the renewal we retired.”
Long-horizon agents, deterministic memory, capability-gated tool use, eval-gated deploys. The platform is the same whether you're running a wind-tunnel campaign, a chip signoff, or a months-long active-learning loop.
Plans that run for hours, then days, then weeks. Deterministic memory, reversible tool calls, explicit checkpoints — so a multi-day campaign doesn't dissolve into a black-box trace.
Every tool call is gated by an explicit capability the model has to request and your policy has to grant. The grant is logged. The refusal corpus is versioned alongside the model.
Each agent ships with a regression suite that runs on every commit and replays historical traces. Synthetic adversarial cases run against every release. Promotion is gated on eval results, not vibes.
An immutable per-run trace, written as you go. The same prompt and the same world produces the same plan. When something goes wrong, you can replay the exact decision the agent made.
Managed cloud, your VPC, on-prem, or air-gapped behind a regulator's boundary. Same runtime, same evals, same audit story — different perimeter.
OpenTelemetry-native traces, SIEM-grade audit events, JSONL exports. Built so your security team and your scientists can read the same record.
The same workloads that make this useful — pharma, aerospace, semiconductor, public sector — are the ones with auditors, regulators and standing data boundaries. The platform is built for that.
Dual-use refusals at the model layer, controlled-pathogen gating at the runtime, chain-of-custody on every reagent. Red-teamed against a versioned corpus.
Customer-VPC and on-prem deployments keep training and inference inside your boundary. Air-gapped deployments produce zero outbound traffic.
Immutable run logs, GxP / 21 CFR Part 11 / ALCOA+ patterns where the regulation applies. Exportable as OpenTelemetry, SIEM events or JSONL.
Every output is signed by the model version that produced it. Promotion through eval gates is recorded; old versions are reproducible by hash.
The day-to-day shape of the work the platform supports — across every discipline.
Generative chemistry, structural optimisation, RTL design-space exploration, antibody libraries.
Forward-in-time trajectories across fluid, structural, EM, molecular, quantum and digital systems.
Compare against measured experimental data. Reproducible benchmark cases ship with the platform.
Active-learning agents pick the next experiment; capability gating audits every tool call.
Drive instruments — liquid handlers, plate readers, foundry hand-off — under your policy.
Immutable trace per decision; export as OpenTelemetry, SIEM events or JSONL.
We pilot first. If we aren't better on the metric you picked by the end of the quarter, we say so and the rest of the quarter is on us. Most pilots promote.
Pick one workload — the renewal you'd rather not sign, the campaign you've been putting off, the chip block you keep postponing. We agree the comparison data, the boundary, and the success metric.
We stand up Aether in your deployment of choice, integrate the data we agreed on, and run the workload alongside your incumbent. You see every trace.
We co-author the comparison memo. If we're not better on the metric you picked, we say so and you keep the platform for free for the rest of the quarter.
Production deploy with eval-gated promotion, on-call coverage, change-management aligned to your release calendar.
These are the cases we're allowed to talk about — the renewals retired, the loops closed, the boundaries respected. The pattern repeats.
Retired a $1.8M CAE renewal across two quarters.
Closed the discovery loop on a fibrosis programme.
RTL to signoff on a 4nm SoC — without an incumbent-EDA renewal.
Aether is the product. Below is how the same model shows up — first as horizontal capabilities, then per industry. Same weights, same runtime, same safety story; different workloads, different agents, different pilot patterns.
Prompt-to-app — agents, sims and UIs, deployable in a click.
Compute, GPUs, data and serving — managed to air-gapped.
Build a living, multiphysics twin of any system — synced to reality.
Topology optimization with simulation in the loop — physics-true, DfM-aware.
Replaces the incumbent editor-embedded coding agents.
SAST, SCA, DAST, IAST, RASP, secrets, IaC, API and supply chain — one platform.
EDR, NGAV, SIEM, SOAR, ITDR, email, CASB and copilot — one platform.
Image scanning, admission control, eBPF runtime detection and enforcement.
Collection, a threat graph, malware analysis and push-to-controls.
Passive discovery, OT DPI, anomaly & ICS threat detection, segmentation.
Discovery, classification, DSPM, access governance and DLP.
ZTNA, SWG, CASB, FWaaS and DLP on one policy engine.
Forward-rolls a digital twin of your attack surface.
Couples a network twin with a physics twin to forward-roll an attack's physical consequence.
Drives liquid handlers, plate readers and your LIMS.
Replaces the incumbent commercial CAE suite.
Replaces the incumbent commercial EDA suite.
Replaces the incumbent computational-chemistry suite.
Inverts discovery — from a spec to a qualified material.
Forward-rolls the physics embodied policies learn in.
RF propagation, RAN optimization and network slicing on one model.
Documentation, models, evals, security and pricing live as full surfaces. Pick a thread.
Sizes, context, modalities, training data.
Evals, refusals, known limits.
REST and gRPC surfaces with versioning.
Plan tiers and enterprise terms.
Papers, benchmarks, replications.
Every release on one page.
Controls, certifications, deployment.
Terms in plain language.
Start with one workload — the renewal you'd rather not sign, the campaign you've been putting off. We'll come back with a scoped pilot.