01 · DISTRIBUTION
Marketplace & procurement
Use cloud or data marketplaces when a current DataKnobs listing and the customer's procurement model align.
Azure · Google Cloud · Databricks Cloud, data & AI ecosystem
Build with DataKnobs in the ecosystem you already use.
DataKnobs is designed for enterprise choice: deploy into customer-owned cloud and data environments, use marketplace procurement paths where available, and combine the right infrastructure, models and data platforms without making one vendor the center of the architecture.
Ecosystem model
Not every relationship serves the same purpose.
The original page grouped marketplaces, compatibility and accelerator relationships under one “partnership” label. The clearer model is to distinguish the job each ecosystem connection performs for customers.
02 · DEPLOYMENT
Customer-owned infrastructure
Deploy into the customer's approved cloud, network, identity, storage and model environment instead of forcing a hosted SaaS boundary.
Azure · GCP · AWS · private cloud03 · DATA PLATFORM
Data-platform integration
Bring DataKnobs intelligence, controls and evaluation close to enterprise data rather than copying every workload into a new system.
Databricks · cloud data services04 · ENABLEMENT
AI technology ecosystem
Use accelerator and technology ecosystems to improve access to AI infrastructure, expertise and technical innovation.
NVIDIA InceptionExplore
How each ecosystem relationship fits.
Select an ecosystem to see the customer value, the type of relationship, and the most appropriate way to use it.
AZ
Microsoft Azure
MARKETPLACE + CUSTOMER-OWNED DEPLOYMENT
Azure can serve two different roles: a commercial route through Microsoft marketplace programs when an applicable DataKnobs offer is available, and an infrastructure boundary for enterprise deployments that need Azure-native networking, identity and governance.
Best fitMicrosoft-centric enterprises, regulated environments and teams that prefer customer-owned Azure infrastructure.
Customer valueAlign deployment with existing cloud controls and use marketplace procurement when it improves the buying process.
DataKnobs roleKREATE, KONTROLS and KNOBS provide the application, governance, evaluation and optimization layers.
Related serviceAzure Marketplace publishing support for companies publishing their own offers.
KreateWebsitesKreateBotsKreate KnowledgeAI TwinAB Experiment
GC
Google Cloud
MARKETPLACE + CUSTOMER-OWNED DEPLOYMENT
Google Cloud provides another path for organizations that want DataKnobs capabilities close to their existing GCP data, model and application services, with marketplace procurement available for applicable listings.
Best fitOrganizations standardized on Google Cloud, BigQuery, Vertex AI or GCP security and networking patterns.
Customer valueKeep workloads within the approved GCP boundary while adding reusable DataKnobs intelligence and controls.
Architecture principleThe cloud remains infrastructure; enterprise context, data, controls and measurable knobs remain the durable application layer.
Related serviceGoogle Cloud Marketplace publishing support for ISVs.
KreateWebsitesKreateBotsKreate KnowledgeAI TwinAB Experiment
AWS
Amazon Web Services
CUSTOMER-OWNED DEPLOYMENT ENVIRONMENT
AWS is best described here as a supported customer infrastructure environment rather than automatically as a DataKnobs marketplace channel. That distinction keeps the page accurate and focuses on what matters to customers: deployability inside their approved architecture.
Best fitOrganizations whose data, applications and security controls already live primarily on AWS.
Customer valueAvoid unnecessary migration and integrate DataKnobs into existing compute, storage, identity and data services.
Commercial pathDirect engagement or another agreed procurement route can be used when a marketplace listing is not the selected path.
Design goalPreserve portability and reduce dependency on a single cloud-specific application architecture.
NV
NVIDIA
INCEPTION / TECHNOLOGY ECOSYSTEM
DataKnobs describes its NVIDIA relationship through the NVIDIA Inception program. This is an AI technology and startup-ecosystem relationship: not a software distribution channel: and is most relevant to technical enablement and AI infrastructure innovation.
Best fitAI workloads where accelerated computing, model performance or GPU-based experimentation are important.
Customer valueDataKnobs can design solutions that take advantage of modern AI infrastructure while keeping business logic portable.
Relevant workloadsIndustrial AI, predictive systems, GenAI and other compute-intensive model workflows.
Relationship typeTechnology/startup ecosystem enablement rather than marketplace procurement.
DB
Databricks
DATA PLATFORM + MARKETPLACE PATH
Databricks is especially relevant when the enterprise data and ML operating model already centers on a lakehouse. DataKnobs can bring experimentation, predictive intelligence and governed AI workflows close to that data environment.
Best fitData and ML teams already operating on Databricks who want reusable application, evaluation or predictive-maintenance patterns.
Customer valueReduce data movement and make AI capabilities easier to evaluate in the platform teams already use.
DataKnobs-described listingsAB Experiment and Predictive Maintenance are presented in DataKnobs ecosystem materials as Databricks Marketplace offerings.
Adoption patternStart with a focused data/ML workflow, then expand into governed applications or broader DataKnobs capabilities.
AB ExperimentPredictive Maintenance
Marketplace catalogs and program status can change. Validate the current listing, region, plan and transaction eligibility during procurement.
Availability
Separate “available to deploy” from “listed in a marketplace.”
A multi-cloud architecture should not imply that every product is transactable through every cloud marketplace. This matrix makes the difference explicit.
| Capability / solution | Azure | Google Cloud | AWS | Databricks |
|---|---|---|---|---|
| KreateWebsites | ● Marketplace path* | ● Marketplace path* | ● Direct deployment | : |
| KreateBots | ● Marketplace path* | ● Marketplace path* | ● Direct deployment | : |
| Kreate Knowledge | ● Marketplace path* | ● Marketplace path* | ● Direct deployment | : |
| AI Twin | ● Marketplace path* | ● Marketplace path* | ● Direct deployment | : |
| AB Experiment | ● Marketplace path* | ● Marketplace path* | ● Direct deployment | ● Marketplace path* |
| Predictive Maintenance | ● Solution deployment | ● Solution deployment | ● Solution deployment | ● Marketplace path* |
*Marketplace path reflects DataKnobs ecosystem materials and should be confirmed against the current marketplace catalog before purchase. Direct deployment means the capability can be implemented in the customer environment without implying marketplace transacting.
Why it matters
The value is architectural choice: not logo count.
For enterprise buyers, a healthy ecosystem strategy reduces friction while keeping data, governance and operating-model decisions under customer control.
Keep data inside the approved boundary
Enterprise deployments can run where security, IAM, networking and data governance already exist.
- Customer-owned cloud contracts
- Private networking and enterprise IAM
- Existing data-platform investments
Choose procurement independently of architecture
A marketplace can be a useful commercial route, but it should not dictate the solution architecture.
- Marketplace where eligible
- Direct delivery when more appropriate
- Different route for different product or region
Move the intelligence layer closer to context
DataKnobs focuses on enterprise context, data, governance and measurable controls instead of treating the foundation model as the whole product.
- KREATE builds capabilities
- KONTROLS governs behavior and risk
- KNOBS enables evaluation and adjustment
Answer in one sentence:
DataKnobs is designed to sit above infrastructure choices, so enterprises can build and govern AI products in the cloud, data platform and procurement ecosystem that fits their existing operating model.
FAQ
Common ecosystem questions.
Does DataKnobs require one specific cloud?
No. DataKnobs is designed to work with customer-owned infrastructure and can be deployed into approved Azure, Google Cloud, AWS, data-platform and private-cloud environments based on architecture and governance requirements.
Are all DataKnobs products available through every marketplace?
No. Marketplace availability varies by platform, region, product and plan. DataKnobs can also deploy directly into a customer's approved environment when marketplace procurement is not the preferred route.
What is the difference between a marketplace relationship and technical compatibility?
A marketplace relationship is primarily a distribution and procurement path. Technical compatibility means DataKnobs can run in or integrate with that environment even if the product is not purchased through that marketplace.
What is NVIDIA's role in the ecosystem?
DataKnobs describes its NVIDIA relationship through the NVIDIA Inception program. It is best understood as technology and startup-ecosystem enablement rather than a software marketplace channel.
Can DataKnobs be deployed into our existing enterprise account?
Yes, customer-owned infrastructure is the preferred model for many larger or regulated organizations because the customer keeps control of cloud, storage, networking, identity and model contracts.
Choose the deployment path that fits your enterprise.
We can start with your cloud, data platform, security boundary and procurement constraints, then map the right DataKnobs architecture and commercial route.