FAQs

Vectara is an agent platform built to meet enterprise requirements for security, accuracy, scalability, and observability. It is available as a service on-premises, within your VPC, or via SaaS. Companies leverage Vectara as a centralized agent platform to build multiple agents to solve a multitude of use cases on a common core data infrastructure, enabling any organization to build quickly, deploy without heavy engineering, and scale across multiple workloads and business units.

RAG foundation

Vectara's agents achieve their high performance by retrieving the right data at the right time. This strong retrieval foundation also happens to form the core component of a Retrieval-Augmented Generation (RAG) system, in which an LLM converts search results into a summary. Many of Vectara's customers have implemented effective enterprise search and RAG-based applications on top of Vectara. Over time, we've found this also enables these customers to find opportunities to build agents on our platform, sometimes applied to the very same or similar workloads.

How does Vectara work?

Vectara comes out-of-the-box with a number of powerful agent tools. Vectara employs agentic extraction from documents, neural and lexical search, knowledge re-ranking, and customized generation. Vectara comes standard with custom models for accuracy and precision during knowledge retrieval, but the platform also allows organizations to utilize any models they deem fit for their discrete business needs.

Vectara is also built to handle siloed and messy data sets, the kind that are inherent in many modern organizations. It does especially well with multi-modal data, which combines text, tables, images, and graphical content. It is by ingesting all of this knowledge that Vectara can place questions in the right context. Vectara scales to meet the demands on companies with large and scaling data sets without redesign.

How can I benefit from Vectara?

You can benefit from Vectara if:

You are looking to build conversational AI agents on your domain data.
You are looking to build a centralized AI agent platformto boost productivity and automate information delivery.
You need Guardian Agents to build out your always-on AI governance.

What are the use cases for Vectara?

Vectara's flexibility enables it to be applied to a wide range of use cases. Typically these use cases take the form of AI agents, RAG applications, or search interfaces. These deployments work well for workloads such as:

Failure analysis
IT service management
Knowledge search
Customer support
Legal document analysis
Document generation

How is Vectara different from other Agentic solutions?

Unlike other agent platforms on the market, Vectara is focused on high-accuracy and tightly governed agentic workloads. Vectara delivers all generated agent answers and actions with a factual consistency score and advanced tool validation. This ensures that businesses can trust their agents to act autonomously with the highest possible fidelity. When agents deliver subpar results, there is a clear audit trail for remediation and learning, which helps address governance and policy concerns. Vectara is more than a simple agentic framework, but a mature enterprise-ready platform for agent development through an advanced API. Vectara scales to meet the demands on companies with large and scaling data sets without redesign.

Vectara agents are unique in that they are able to operate in production without a major investment in additional engineering and without the high cost of DIY projects. Many agent platforms provide frameworks for building POC agents that often fail in production. Vectara comes with many tools out of the box and also supports builders bringing their own tools that agents can utilize. Vectara allows you to build once and deploy fast.

Is Vectara a vector database?

No, Vectara is not a vector database. It is an AI Agent 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 an AI agent platform that includes multiple components required for RAG, tool calling, APi tasks, document processing engines, 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.

On-premises installs are currently available for the North America, APAC, and the UAE regions only.

How do I apply for a job at Vectara?

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

Software

How do I get up and running with Vectara?

All you need to do is sign up for a 30-day free trial 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?

For simple use cases, setting up and implementing Vectara in production can be done in a few days. Index your first document and issue your first batch of queries in under 5 minutes. More sophisticated deployments typically take weeks.

Does Vectara's offering come with onboarding and training?

Yes, as part of all plans, users will receive onboarding and training within the scope of their first use case. Resources for training are delivered through online platforms and individual engineer training as part of production implementation.

Which models does Vectara support?

Vectara provides a bring-your-own-model approach supplemented by a wide range of out-of-the-box models.

With Vectara, customers can integrate LLMs from these providers:

OpenAI compatible, e.g. OpenAI, Azure OpenAI, OpenRouter, vLLM-hosted, or your own self-hosted models. Includes models such as GLM, Minimax, and Grok.
Anthropic, e.g. Claude via Anthropic, AWS Bedrock, or Vertex AI.
Vertex AI, e.g. Google Gemini.

Which 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, Common Mark, and image data. Tables and diagrams are supported. Audio data support (via a speech-to-text engine) is available upon request by reaching out to support@vectara.com.

Which 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-premises. 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 contact Vectara support directly at support@vectara.com.

Paying customers can access our Support Portal at 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 three Vectara Enterprise subscription plans to choose from: SaaS, VPC, and On-prem. Customers can also add Forward-Deployed AI Engineers or subscribe to Platinum Support services.

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. There is no free-forever program.

Which payment methods and currencies are accepted by Vectara?

Vectara accepts payments made through contracted agreements. Vectara supports billing in United States Dollars (USD).

Is there any commitment once I start paying for Vectara?

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

How do I switch from one plan to another?

To upgrade your plan, please reach out directly to sales@vectara.com.

How can I change my account details?

Account details 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.

SOC II Compliance

Vectara’s platform is independently validated through annual SOC 2 Type II audits and HIPAA compliance, ensuring our data protection and security practices meet the highest standards. Customer data is always encrypted in transit and at rest, with backup and disaster recovery programs tested regularly. We continuously monitor for vulnerabilities, conduct penetration tests, and follow strict SLAs for remediation. These controls give our customers confidence that their data remains protected, resilient, and available.

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 Partner program?

Today, we have offerings for Referral Partners, Resellers / VARs, Systems Integrators, Original Equipment Manufacturers (OEMs), and Managed Service Providers (MSPs). Any technology business partners looking to drive demand generation, co-selling, consulting services or bundled integrations are encouraged to reach out!