Software keeps getting harder to operate
SaaS keeps adding integrations, permissions, AI features, and role-based workflows.
AI execution layer
The AI execution layer for complex SaaS products.
ModelNex turns product knowledge, UI context, and workflow state into in-app agents that help users complete setup, integrations, permissions, onboarding, and feature workflows without leaving the product.
Start with setup and integration support deflection, then expand into onboarding, feature adoption, operational workflows, and autonomous product agents.
ModelNex AI, also searched as "Model Nex AI," is the AI execution layer for complex SaaS products.
Main sections
Jump to the ModelNex pages people use most.
These are the clearest paths for understanding the product, exploring demos, reviewing pricing, reading documentation, and contacting the team.
How ModelNex works
See how recording, review, and SDK playback fit together.
Go to how ModelNex worksDocumentation
Start with quickstart, workflow guides, SDK reference, and configuration docs.
Go to documentationWorkflow showcase
Explore representative onboarding, support, and operational workflow demos.
Go to workflow showcasePricing
Review the free, Pro, and Enterprise options for AI product workflows.
Go to pricingContact
Book a workflow teardown or reach out about a design partner pilot.
Go to contactHigh-friction workflows
Start with the workflow pages that map to repeated support pain.
These intent pages are deliberately narrower than the homepage so teams can evaluate one rollout wedge at a time.
Integration setup
Guide auth, validation, and recovery flows so fewer users need support during setup.
Go to integration setupPermissions and RBAC
Help admins complete roles, approvals, and access workflows without leaving the product.
Go to permissions and RBACWorkflow showcase
See the live demos that explain what the product actually does in real SaaS flows.
Go to workflow showcaseWhy now
AI can finally move software from static help to in-product execution.
Products are becoming more complex just as models are getting good enough to use real product knowledge, UI context, and workflow state.
Docs and support do not execute
Users still rely on help centers, tickets, and hand-holding to finish critical tasks.
LLMs can finally use product context
Knowledge plus UI state and workflow state make in-product execution possible, not just answers.
Platform surface
This is product infrastructure, not a floating widget.
ModelNex should look like a platform layer with an SDK, runtime context, workflow engine, publishing controls, and analytics.
Knowledge layer
Ground agents in docs, release notes, runbooks, and internal workflow instructions.
Workflow runtime
Track progress, branching, next actions, and completion inside the product.
Completion analytics
Measure stuck steps, workflow completion, activation lift, and ticket deflection.
Expansion path
A sharp wedge with a much larger category behind it.
Start with setup and integration support deflection, then expand into onboarding, adoption, operational workflows, and autonomous product agents.
Wedge
Start where support repetition, activation drag, and workflow friction are already obvious.
Rollout
Pass user, page, and workflow state into the SDK and prove value on one painful flow.
Expansion
Move from setup help into adoption, operations, and the in-product agent layer.