FAQs

About Vectara

What is Vectara?

Vectara is an end-to-end platform that empowers product builders to embed powerful Generative AI features into their applications with extraordinary results. Built on a solid hybrid search core, Vectara delivers the shortest path to an answer or action through a safe, secure, and trusted entry point. Vectara is built for product managers and developers with an easily leveraged API that gives full access to the platform’s powerful features. Vectara’s Retrieval Augmented Generation (RAG) allows businesses to quickly, safely, and affordably integrate best-in-class conversational AI and question-answering into their application. Vectara never trains its models on customer data, allowing businesses to embed generative AI capabilities without the risk of data or privacy violations.

How does Vectara work?

Vectara is RAG-as-a-service, encapsulating the various components required for a scalable and high-performance RAG pipeline (document processing, multiple best-in-class embedding models, a retrieval engine, multiple rerankers to unlock different capabilities for your app, and an LLM) behind an easy-to-use developer API. Developers use Vectara to build RAG and semantic search applications by using the API to index their documents and respond to user queries with the full power of RAG, while Vectara works behind the scenes to execute the RAG ingest and query flows in a secure and scalable way while maintaining low latency and low TCO.

How can I benefit from Vectara?

You can benefit from Vectara if:

You are looking to build a chatbot based on your documents and data.
You are looking to build a question-answer system to boost productivity and automate information delivery.
You need AI-based summarization with world-class retrieval performance.

What are the use cases for Vectara?

AI Assistants
Retrieval Augmented Generation (RAG)
Question and Answering Systems
AI Agents

How is Vectara different from other GenAI solutions?

Vectara gives all types of builders an end-to-end platform for embedding powerful generative AI capabilities into your app or site without the need for data science and machine learning experience.

Some of Vectara’s unique differentiators include:

End-to-End RAG Platform: Vectara is an end-to-end platform for serverless RAG, expertly tuned and always available.
Quick Time to Value: Vectara is a trusted partner for companies that brings powerful generative AI tooling to all types of developers and business users. Vectara helps companies turn deployments from years to weeks.
Ultimate Trust and Control: Vectara also provides a factual consistency score (FCS) with every response and many ways to configure your queries and responses.

Is Vectara a vector database?

No, Vectara is not a vector database. It is a RAG-as-a-service platform that includes multiple components required for RAG, such as a document processing engine, chunking, a state-of-the-art embedding model, and its own internal vector database, which is used by its high-quality retrieval engine.

Is Vectara an embedding service?

No, Vectara is not an embedding service, although it does have state-of-the-art embedding models it uses within the platform. It is a RAG-as-a-service platform that includes multiple components required for RAG, such as a document processing engine, chunking, state-of-the-art embedding models, and its own internal vector database, which is used by its high-quality retrieval engine.

In which countries is Vectara available?

Vectara is a cloud-based GenAI platform running on AWS or GCP infrastructure in Vectara’s SaaS environment or alternatively in your own VPC or on-premise install. Vectara can be deployed in most regions in AWS or GCP. See the AWS Regional Services and GCP Regions/Zones pages for more details. Reach out to sales@vectara.com if you have specific requirements.

How do I apply for a job at Vectara?

You can check all our available openings on our Careers page.

What is Retrieval Augmented Generation or RAG?

Retrieval Augmented Generation, otherwise known as RAG, is an approach to building GenAI applications that builds on semantic search (or retrieval) to provide answers to user questions by retrieving the most relevant facts and providing them to a generative LLM for summarization. This approach has several advantages:

It reduces GenAI costs by telling the LLM to only use relevant information when providing answers instead of providing much larger amounts of data.
It drastically reduces hallucinations, copyright issues, and keeps answers focused on the types of answers you’d want to provide in your business because it only uses the LLM for its knowledge of language: not for knowledge of how to answer end user questions. The answers to the questions come from the data you provide.
It increases GenAI security, since ACLs can be used for filtering data out that the user does not have access to before it ever gets to the LLM.
It provides explainability of GenAI responses by citing references to where it found the answers.
It keeps information up-to-date and eliminates costly, time-consuming, and privacy-concerning fine tuning based on your enterprise data. Information can be added and removed in seconds just as it would with a traditional keyword search application.

Software

How do I get up and running with Vectara?

All you need to do is sign up with a company email address. You will then get access to the Vectara Console to get started with ingesting documents and testing the platform.

For more information on setting up Vectara, you can check out our Docs.

How long does it take to implement Vectara?

Setting up and implementing Vectara in production can be done on the same day. Index your first document and issue your first batch of queries in under 5 minutes.

What file types does Vectara support?

Vectara’s file upload API supports PDF, Microsoft Word, Microsoft Powerpoint, Open Office, HTML, JSON, XML, email in RFC822, text, RTF, ePUB, and Common Mark. Audio data (via a speech-to-text engine) and image data (via optical character recognition – or OCR) are available upon request by reaching out to support@vectara.com.

What languages does Vectara support?

Vectara supports over 100 languages and dialects. This support is integrated across the platform, including data ingest, the embedding models, retrieval and generation with the LLM.

Can I index from any data source?

You can index data from any supported file format, as well as raw text from data source systems, via Vectara APIs or the file upload feature within the Vectara Console.

Can I search across multiple indexes?

Yes, you can issue a single query or multiple queries in parallel to one or multiple indexes.

Deployment

What are the deployment options for Vectara?

Vectara is available as a fully managed cloud platform, maintained by the Vectara team, in a VPC install, or on premise. Like other multi-tenant SaaS services, Vectara’s SaaS platform employs a release process designed to ensure features ship faster, the product can scale seamlessly when any client load increases and it leverages enterprise-grade security. This eliminates the responsibility for server maintenance, upgrades and capacity provisioning.

What resources do I need to deploy Vectara?

No additional or specialized engineering, hardware, or infrastructure resources are needed to successfully deploy Vectara if you use our SaaS service. Vectara was developed to make it easy for web and application developers to integrate generative AI in sites and applications without the need for additional training or resources.

For more information on setting up Vectara, you can check out our Docs.

Running in a VPC on self-managed/on-premise install requires resources to be allocated that depend on your specific usage and data requirements. If you need a VPC or on-premise install, reach out to sales@vectara.com to let us help size the right resources for your use case.

Does Vectara have any scalability limits?

Vectara can autoscale from small text volumes to millions of documents. Our SaaS platform automatically adds capacity as needed to handle higher query volumes.

I'm having trouble setting up Vectara. What should I do?

If you are having any trouble setting up Vectara or need any help with implementation, you can send a message on our Vectara Discuss Community or contact Vectara support directly at support@vectara.com.

You can also visit https://support.vectara.com.

What are Vectara’s SLAs?

Vectara offers SLAs in support, availability, and performance.

For a full list of available Vectara SLAs, please review our Pricing page and order form documents. If you have more aggressive SLA needs, we often can meet them: reach out to sales@vectara.com to start the conversation.

Pricing

What are the different options for buying Vectara?

There are several Vectara SaaS subscription plans to choose from: Standard, Pro, and Enterprise. Vectara also offers VPC and on-premise options.

You can visit Vectara’s pricing page to view the different features for each plan and determine the best one for your needs.

Is there a free plan?

Vectara offers a 30-day free trial complete with nearly all of the enterprise features of the platform.

What is Vectara’s pricing model?

Vectara's pricing model is usage-based and based on the number of search queries processed and account size. Visit our pricing page for more details.

How do you count queries in your pricing model?

Any queries that are issued to indexed content – via the Vectara console or the Vectara API – are counted towards the query count.

What is the definition of account size in the pricing model?

Account size is the sum of text and metadata size (measured in MB) within all corpora in the customer account, before any replication factor is applied.

How does billing work?

Details on how our SaaS product billing works, see the SaaS billing policy page.

Which payment methods and currencies are accepted by Vectara?

Vectara accepts payments made through a credit card or on the AWS Marketplace to use AWS credits. Vectara supports billing in United States Dollar (USD).

Is there any commitment once I start paying for Vectara?

Each plan has its own minimum commitment. For details, see our pricing page.

What happens if I exceed my committed plan usage?

Once you have exceeded the minimum commitment, you will automatically be billed for any additional bundles you have consumed at the end of the month.

How do I switch from one plan to another?

Some upgrade functions can be performed directly within the Vectara Console. For any other requests, please reach out directly to sales@vectara.com.

How can I change my account details and billing information?

Account details and billing information can be accessed and changed from the Billing tab within the Vectara Console.

Security and privacy

How does Vectara handle and process sensitive personal and customer information?

Vectara supports full client control over how data is preserved, including the support of a full deletion of customer data via API. Clients decide what data they transmit to the service and what data remains within the service, with the exception of billing and billing contact data.

Does Vectara implement any encryption standards for information processing?

Vectara ensures sensitive data is encrypted and the keys are managed both logically and physically by the appropriate teams.

Encryption at rest is AES 256-bit symmetric key encryption. Separate keys are managed per corpus, and access to keys is through an account master key managed on FIPS 140-2 compliant hardware. Vectara also provides the option of a customer managed account master key. Encryption in transit is TLS 1.3.

Does Vectara have a security program?

Vectara has a documented security program that is audited periodically for major security program objectives, status of security program non conformities, and risk logs. The system architecture was designed to enable ready compliance with SOC 2 and ISO 27001 standards. Vectara systems are SOC 2 and HIPAA compliant. Vectara’s SOC 2 Type 2 and HIPAA Evaluation Report are available in the Vectara Trust Center. If you would like to report a security concern, contact security@vectara.com.

Does Vectara have a privacy policy?

Vectara has a documented privacy policy that is reviewed periodically. Vectara’s privacy policy covers responsibilities under GDPR regulations. CCPA regulations are not applicable to Vectara. Vectara’s privacy policy can be found here.

Does Vectara have a disaster recovery plan?

Vectara has policies and procedures for disaster recovery and backup. Vectara has established, documented, implemented, and maintained processes, procedures, and controls to ensure the required level of continuity for information security during an adverse situation.

Information processing facilities, infrastructure, and application architecture are implemented with redundancy sufficient to meet and support high availability requirements.

Is Vectara HIPAA compliant?

Yes, Vectara is SOC 2 Type 2 and HIPAA compliant. You can request access to Vectara’s SOC 2 Type 2 and HIPAA Evaluation Report in the Vectara Trust Center.

Partnerships and startups

What type of partners can join Vectara’s Ecosystem Partnerships program?

Vectara’s Ecosystem Partnerships program is designed with focus on co-creating value for mutual end-customers. Any technology or business partners looking to drive additive integrations and go-to-market motions in GenAI are encouraged to apply.

How does Vectara support Startup Partners?

Startup Partnerships play a pivotal role in Vectara’s Partner Ecosystem to drive co-innovation, and our aim is to empower startups to accelerate time to market in GenAI. Approved startups are provided with the full power of Vectara’s platform, financial incentive (up to $5,000 in one-time credits & discounts) to get started, a tailored success journey, and value-based benefits to differentiate your business with Vectara’s Trusted GenAI Platform. Learn more at vectara.com/startups.

I’m not sure if my startup qualifies, how should I proceed?

Any startup embarking on a GenAI journey and looking to develop RAG enabled applications, products, or chatbots are encouraged to apply. Please submit a Startup application and we’ll be in touch!

What’s expected of a Startup Partner to participate?

Aiming for mutual success, we’ll collaborate on your requirements to extend an appropriate startup offer based on your capacity needs, and provision your account accordingly. We ask for your proactive engagement in the program and milestone based journey, proper utilization of Vectara’s platform and consumption of credits within 12 months, and collaboration on co-marketing activities upon launch of jointly integrated MVP/Solution. As the success journey nears completion, we’ll discuss commercial arrangements to continue your ongoing production needs with Vectara.