RapidCanvas

Unify your data and unlock what’s possible.

RapidCanvas is an agentic AI platform that lets enterprises build, deploy, govern, and operate AI agents on their existing data and systems. We pair the software with vertical experts and PhD data scientists to help teams reach production AI in weeks, not months.

Expert-led AI Workshop
Book a Discovery CallComplimentary 30-min call to assess fit
G2 Winter 2026 awards
G24.9 out of 5
Gartner Peer Insights5.0 out of 5
Watch the RapidCanvas platform overview
Architecture

The full stack at a glance.

Enterprise Solutions on top. Context Engine in the middle. Platform × Delivery underneath—all supported by an enterprise-grade foundation.

RapidCanvas platform architecture: Enterprise Solutions, Context Engine, Platform and Delivery, on an enterprise-ready foundation

The delivery lifecycle.

From the system of record to the moment of decision. A single engine spans all four stages: no hand-off between tools, no re-platforming to get from pilot to production, and one set of controls end to end. Select a stage to see which capabilities carry it.

Design AI solutions

Business-language specs in. Governed workflows out.

Describe the decision in plain business terms; the platform builds the pipelines, models, and safeguards behind the scenes. Automated agents help translate requirements and validate outputs. For deeper control, Canvas provides structured workflows, versioning, and reusable components. Every step is traceable and explainable.

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Connect all data and knowledge

No migration. No mirroring. Context follows.

We don’t alter or move your data sets and knowledge assets. We just teach them how to talk. Your Enterprise Context Engine organizes as it connects, and rather than a generic model, you get a custom system born from how your business actually works.

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Launch AI solutions

Easy integration to any cloud or environment.

The platform runs reliably wherever you need it (AWS, Azure, or GCP). Deploy anywhere—your cloud, a managed setup, or SaaS—and connect directly to the systems your teams already depend on (APIs, applications, or write-backs into ERP, CRM, and ticketing tools, etc). Your AI goes wherever your work already happens, and updates are fast, low-risk, and never require starting over.

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Governance built in, not bolted on

One platform for hosting, security, evaluation, and cost.

Run AI as a managed enterprise system, not a set of disconnected deployments. Built-in compliance (SOC 2 Type II, HIPAA, GDPR, ISO 42001) stays in place regardless of where you run it, so your teams can move fast without the risk of flying blind. Monitoring and visibility keep you informed on what’s running, how it’s performing, and what it’s costing, all in one place.

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Five capabilities make it different.

What you build may change. What powers it stays consistent.

Enterprise Context Engine™

The foundation. Your organization’s knowledge, structured and accessible for every AI-driven decision.

Skills

The library. Reusable capabilities that work across functions, with domain-specific depth where needed.

Compounding Intelligence

The flywheel. Each solution builds on the last, accelerating future outcomes.

Evaluation & AI Ops

The proof. Every output is tested, traceable, and reliable.

Hybrid Approach™

The execution. Structured where precision matters, adaptive where it drives scale.

What’s new in the platform.

Recent releases bring broad improvements across the platform—streamlining workflows, strengthening reliability, and helping teams move faster from setup to decisions.

September 15, 2026

Built for Business Impact: Context That Reaches Where Work Happens

The Context Engine now draws from the tools teams actually work in, including Slack and Google Drive, so the conversations and documents where decisions get made become part of a project's context. The CLI also sets up AI coding agents on its own, generating the project context they need to work inside your codebase without configuration.

September 7, 2026

Built for Business Impact: Every Connector Becomes Editable Code

Connector and destination nodes become Recipe Nodes, so the query behind any source is open to edit, filter, join and rerun until the dataset is right. Scenarios let one pipeline run under different configurations without touching the recipe, and an AI-generated diagnosis reads a server's own telemetry to name the likely cause when something fails.

August 17, 2026

Built for Business Impact: One View of Every Project

A new Project Overview page brings a project's live assets, resources and run status into one place, so the state of the work is visible without opening it. Secrets move to the project level so access stays scoped to the work it belongs to, and the CLI authenticates with an API key.

Got questions? We're here to answer them for you

Have more questions?
Contact our support team to get what you need.

RapidCanvas is an agentic AI platform that lets enterprises build, deploy, govern, and operate AI agents on their existing data and systems. The software is paired with vertical experts and PhD data scientists, so teams reach production AI in weeks rather than months.
No. RapidCanvas does not alter, move, or mirror your data sets and knowledge assets. It connects to them where they already live, and your Enterprise Context Engine organizes that knowledge as it connects.
On AWS, Azure, or GCP. Deploy in your own cloud, a managed environment, or as SaaS, and connect directly to the systems your teams already depend on through APIs, applications, and write-backs into ERP, CRM, and ticketing tools.
SOC 2 Type II, HIPAA, GDPR, and ISO 42001. Those controls stay in place regardless of where you choose to run the platform.
The Enterprise Context Engine, which structures your organization’s knowledge for every AI-driven decision; Skills, the reusable library that works across functions with domain-specific depth; Compounding Intelligence, where each solution builds on the last; Evaluation and AI Ops, so every output is tested and traceable; and the Hybrid Approach, structured where precision matters and adaptive where it drives scale.
Four stages. Design the solution from business-language specs, connect data and knowledge without migration, launch into your cloud and existing systems, and govern hosting, security, evaluation, and cost from one place.
No. The platform is model-agnostic and works with your existing enterprise infrastructure rather than replacing it.
Weeks rather than months. Engagements typically start with a two-day expert-led workshop that produces a tailored AI roadmap with ROI-prioritized use cases, and 100% of the workshop cost credits toward a subscription.
Agents that scan, test and act on your data, on a schedule or on demand, alongside models served as APIs your own systems call and applications your operators work in. All three run on the same Context Engine, so they share one understanding of what your data means rather than each carrying its own.
Through the Context Engine and the evaluation layer together. Your schema is mapped once to business meaning, and every call is wrapped with evaluation and lineage, so a figure in an answer carries the field it came from and a decision can be reconstructed during a review.
RapidCanvas
G2 Winter 2026 awards: Momentum Leader, High Performer, Best Support, Users Most Likely To Recommend, Users Love Us
G24.9 out of 5
Gartner Peer Insights5.0 out of 5
Certifications: AICPA SOC, ISO 27001, ISO 45001, GDPR, HIPAA

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