Rapta
Also known as: Rapta Inc, AI Supercoach, SuperPod
Agentic AI manufacturing platform that automates real time QA, computer vision inspection, and worker upskilling for precision aerospace, defense, and medical device production.
Rapta is an agentic AI platform that supercharges US precision manufacturing by automating inspection, quality control, and production scalability for aerospace, defense, medical device, semiconductor, and electronics makers. Its AI Supercoach provides inline, real time QA for both human line workers and robotic processes, catching quality issues as they happen, while training and upskilling operators in real time with video based work instructions so a new worker can become productive in hours and staff can flex across lines. The platform learns a manufacturer's proprietary assembly techniques from just a few correct and incorrect examples using a visual setup tool, then auto generates a production grade AI training set in minutes, aided by a physics engine that produces photorealistic synthetic images of correct and defective parts, versus the months and thousands of manual images legacy vision systems require. Its SuperPod robotic inspection stations add automated, operator free inspection from microns to meters in cleanroom rated environments with full video traceability. Across deployments Rapta reports roughly 30 percent added capacity, up to 98 percent fewer errors, 10x faster task automation, and 3x faster new product introduction, with 100 percent video traceability, defect annotations, and pass or fail records supporting FDA and ISO certification. Supervisors get task level analytics to find bottlenecks and optimize workflows.
Vendor details
Canonical URL
https://rapta.ai
Category
Enterprise operations agent
Funding status
Closed an oversubscribed $2.7M seed round (June 2025) with institutional investors Portland Seed Fund, Phase Shift Ventures, SeedFunders Orlando, and Roadster Capital, plus notable angels Ben Johnson (co-founder of Carbon Black), Ryan Permeh (co-founder of Cylance), Dennis Fritz (founder of DW Fritz Automation), and Joe Dobrenski (former Sequoia partner). Based in Tigard, OR with an East Coast HQ in Cocoa Beach, FL. Selected for the 2025 Northrop Grumman Technology Accelerator; customers include Shimadzu USA, defense primes, and medical device makers.
Company status
independent
Use cases & customers
Primary use cases
Target customers
Deployment options
Integrations
Connects previously siloed engineering, production, and quality processes into a unified feedback loop and offers APIs for data integration with other systems for a comprehensive view of operations. The SuperPod robotic inspection hardware integrates natively with the Supercoach software.
Sources & related URLs
Research sources
Capability coverage
8.5 / 14 capabilities · 61%
| Integrations & Tool CallingConnects siloed engineering, production, and quality processes into one feedback loop, offers APIs for data integration with other systems for a comprehensive operations view, and natively integrates the SuperPod inspection hardware with the Supercoach software. | Full |
|---|---|
| Workflow OrchestrationAutonomous agents orchestrate inspection, quality control, training, and process control workflows, with SuperPod executing programmed inspection paths automatically and a unified feedback loop across engineering, production, and quality. | Full |
| Knowledge Grounding & RAGThe platform learns a manufacturer's proprietary assembly techniques from a few correct and incorrect examples, captures expert video work instructions, and uses a physics engine that understands materials and processes to generate training data, grounding models in the customer's specific processes. | Full |
| Human Oversight & GuardrailsRapta augments and coaches human operators rather than replacing them, flags defects and quality issues in real time for human action, and gives supervisors task level analytics to oversee performance, keeping humans central to production. | Full |
| Security, Identity & GovernancePositions itself as the only secure solution to automate AI deployment for manufacturing, targets defense and aerospace with certification traceability, and was founded and advised by cybersecurity veterans, but specific security certifications for Rapta were not retrieved this session. | Partial |
| Observability & AuditabilityEvery inspection generates a full digital record with 100 percent video traceability, defect annotations, and pass or fail documentation for QA and compliance, plus task level analytics and reporting for supervisors and certification traceability. | Full |
| Memory & State PersistencePersists learned assembly models, work instructions, and operational and training data, and can standardize and replicate assembly know how across manufacturing sites, but no explicit per agent memory construct is documented. | Partial |
| Deployment & Data ResidencyDeploys on the factory floor at the edge, including SuperPod hardware on the line in cleanroom rated environments, which suits defense data control, and can be stood up in under a day, but explicit data residency options are not framed on the retrieved pages. | Partial |
| Prebuilt Agents / Templates / PacksOffers a visual setup tool, prebuilt inspection routines that auto load per assembly type, SuperPod hardware variants, and standardized work instruction templates replicable across sites, but not a broad user composable catalog of agents. | Partial |
| Triggers & Channel CoverageProvides real time inline QA triggered by each part or inspection pass on the line, catching issues as they happen, but trigger and channel coverage is centered on the factory floor and on screen operator interface. | Partial |
| Model Flexibility & RoutingRapta trains and runs its own deep learning vision models on defect data and physics engine synthetic imagery. No customer selectable model or multi provider routing is documented. | Unable to verify |
| APIs / SDKs / MCP ExtensibilityData integration with other systems is possible through APIs for a comprehensive operations view, but no public SDK or MCP surface for building on Rapta is documented on the retrieved pages. | Partial |
| Testing, Debugging & OptimizationA sophisticated MLOps automation pipeline auto generates production grade AI training sets in minutes with physics based augmentations for varying lighting, color, and geometry, supporting rapid model training and validation, though not a general agent evaluation harness. | Partial |
| Browser / Computer-useRapta uses physical world computer vision and robotics (cameras and SuperPod inspection stations on the factory line), which is not browser or GUI based computer use, and no such capability is documented. | Unable to verify |
Pricing
Contact sales; no public pricing. Software plus optional SuperPod hardware, deployed via solution experts and system integrators.
per work cell / per inspection station, plus optional hardware
Cost watchouts
Deployments may include SuperPod inspection hardware (capex) and system integrator services in addition to the software subscription, so total cost extends beyond a per seat fee. Cost likely scales with number of work cells or inspection stations.
Variable cost rationale
Cost scales with number of work cells and inspection stations and can include SuperPod hardware and integrator services, so total spend rises with deployment breadth across a factory.
Sales call required
Yes — required for paid access
Free / trial
No public free tier; virtual demo on request
Lowest paid plan
Not public
Key ambiguities
No public rate card. Split between software subscription, hardware, and integration services is not disclosed.
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