Sold by: TectonÂ
Tecton empowers data practitioners to build new features collaboratively, deploy them to production instantly, and serve them for model training and real-time predictions.
Overview
Tecton's Feature Store manages the complete machine learning feature lifecycle. With Tecton, a data practitioner can get operational ML pipelines past the finish line and into production in minutes rather than months. Tecton makes it easy to access and join data across batch, streaming, and real-time sources, enabling data practitioners to leverage all of their data as reliable assets to power operational ML applications. It does all this while providing the reliability, standardization, and reusability organizations need to scale ML to multiple critical use cases such as fraud detection, personalization, recommendation, ranking, and more.
Why work with us:
Leverage all data assets: Tecton makes it easy to build features using any combination of all your data sources (data warehouses, data lakes, streams, and more) and data types (batch, streaming, and real-time).
Frictionless path to production: Tecton handles the entire feature lifecycle and allows you to deploy features to production in minutes, all with 100% offline/online parity and best-in-class data governance.
Operational excellence: Tecton is purpose built for scale and provides best-in-class enterprise-grade SLAs, security, and monitoring, all off-the-shelf.
Collaboration: Tecton provides all this in a single, centralized platform that allows teams to easily collaborate and re-use existing work.
For a custom, private contract, please contact hello@tecton.ai for a private offer.
Highlights
- Runs on your existing infrastructure
- Fully managed service with SLAs
- Cost effective with no licensing fee
Details
Sold by
Delivery method
Deployed on AWS
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Features and programs
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Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
Tecton Platform Pack | Platform access, onboarding and installation | $10,000.00 |
Dimension | Cost/unit |
|---|---|
1M feature writes | $5.00 |
1M feature reads | $25.00 |
Vendor refund policy
All fees are non-cancellable and non-refundable except as required by law
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
24 x 7 on call support support@tecton.aiÂ
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
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In ML Solutions, Infrastructure as Code, Data Analytics
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In Feature Engineering
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In Time-series Forecasting
AI generated from product descriptions
Feature Lifecycle Management
Manages complete machine learning feature lifecycle from development to production deployment
Multi-Source Data Integration
Supports feature building across batch, streaming, and real-time data sources with cross-source data joining capabilities
Enterprise-Grade Infrastructure
Provides scalable infrastructure with enterprise-level security, monitoring, and service level agreements
Feature Deployment Automation
Enables instant feature deployment with 100% offline and online parity and automated governance
Collaborative Feature Development
Offers centralized platform for data practitioners to collaboratively build, share, and reuse machine learning features
Feature Computation Engine
Rust-based parallel pipeline engine that compiles Python feature definitions for online, streaming, and batch environments
Data Source Integration
Capability to integrate data from multiple APIs and sources for real-time machine learning feature computation
Vector Database and LLM Support
Unified platform supporting structured and unstructured data with vector database and integrations for Retrieval Augmented Generation workflows
Feature Pipeline Monitoring
Automated monitoring of feature pipeline execution and feature distribution with real-time alerting for data drift and pipeline issues
Feature Engineering Experimentation
Dynamic feature pipeline forking and experimentation with instant deployment and visualization of changes
Data Pipeline Management
Supports data sharding, dynamic resource optimization, and prevents data contamination with error correction mechanisms
Model Authoring Capabilities
Provides deep learning features with custom reusable components and automatic dimensionality transformations
Experiment Tracking
Enables hyperparameter tuning, model evaluation, and comprehensive model evolution tracking
Model Registry and Deployment
Offers secure model storage with full traceability and one-click deployment across cloud, on-premises, and edge environments
Security Infrastructure
Implements comprehensive security features to protect data and models throughout the machine learning lifecycle
Standard contract
No
Customer reviews
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1 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Logistics and Supply Chain
Tecton Machine Learning Expert
Reviewed on Aug 04, 2022
Review provided by G2
What do you like best about the product?
best to make automate decisions in simple way
What do you dislike about the product?
no negative point. All features are good
What problems is the product solving and how is that benefiting you?
Time Saving on collate raw data and automate data to provide various outputs