Data Agent

RAG/LLM-based search for your data

With Data Agent, you can effortlessly create a no-code AI chatbot for any use case. The AI bot is trained on your data, easily customisable, and deployable across various channels

A Generative AI chatbot built on your data in a snap

What is aData Agent?

Data Agent is an AI-driven tool for quick conversational access to key data from multiple sources. Integrating with numerous data, it provides fast and straightforward access to crucial data. Data Agent simplifies the data retrieval process, delivering accurate results in real time.

What data can be used?

Data Agent integrates with multiple data sources like weblinks, Google Drive, Dropbox, SharePoint, and leading CRMs to provide deep, contextually correct responses to queries across your data collection. Data Agent makes data retrieval easy, interactive and insightful.

Create your very own Data Agent

Facilitate natural language search

across all data types and sources

  • Knowledge base, product documentation, internal wikis
  • Domain-specific web content
  • Conversations, meeting notes, feedback from customers
  • CRMs, PDFs, DocX
  • MP3 audio files

Effortlessly connect to your data across various channels

Knowledge Base integrations

Automatically update and train your LLM with documents stored in

Communication Channels

Integrate with popular platforms to streamline communication

Define your actual use case and value of Data Agent

Hr and onboarding

Quickly access corporate data

Data Agent can be a potent training tool, providing new hires with instant access to process-related information and solutions to typical queries, greatly reducing their learning curve.

Customer support

Find what your customers need fast

In customer support scenarios, Data Agent can be extremely valuable by providing support representatives with instant access to technical data, helping to decrease response times, enhance customer engagement, and efficiently address customer issues.

Complex documentation

Implement a Q&A bot for your technical data

For handling complex documentation, Data Agent can be a lifeline, swiftly retrieving necessary instructions or specific software details from extensive technical manuals, enhancing efficiency for IT staff in problem-solving tasks. 

Website search

Create an AI bot for website in a snap

Data Agent can help in creating a website bot by rapidly building, fine-tuning, and integrating a chatbot that directly answers visitor queries and navigates them based on the existing website information, resulting in real-time, hassle-free customer interactions and enhanced engagement.


Chat with your CRM data

Data Agent can be a game-changer in sales by swiftly extracting crucial customer preferences or historical purchase data from different CRMs, facilitating personalised sales pitches and enhancing deal closures.

Elevate your AI’s capabilities with our fine-tuning service

We carefully modify pre-developed large language models to fit your unique requirements and goals seamlessly. At Tovie AI, we're committed to ensuring your AI system produces efficient and innovative output, encouraging creative problem-solving in your business.

Data Agent is designed to avoid hallucinations and misleading content. It strictly delivers responses based on your organisation's existing data and ensures factual and relevant information to prevent potential issues.

Define specific use cases for your organisation with our consulting services

To succeed in modern markets, companies must have a clear AI strategy that explores, tests and analyses new ways of applying Generative AI in business.

If you're considering integrating GenAI tools but need help determining where to begin, consult specialists who can assess your business processes and AI readiness.

At Tovie AI, we help organisations develop their AI strategies. We explore your teams, roles, and functions, collaborating to generate ideas.

This process ensures stakeholders understand where generative AI can add value before committing resources.

Learn how Tovie AI leverages Generative AI to optimise new technology benefits for your business in our free guide.


Tovie AI consulting services

Your guide to Generative AI in business

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«Employees spend 1.8 hours a day/9.3 per week searching for relevant information»

McKinsey report

Employee productivity depends on how quickly they can find answers and required information. However, they often experience friction when interacting with company resources.

AI Data Agent for company-specific data enables workers to access and search data quickly and efficiently, enhancing their overall performance and allowing them to focus on high-value activities.

Scale employee expertise

Boost productivity

Promote transparency and accountability

 Why Data Agent

Quick and easy access to information

One of the primary advantages of implementing Data Agent is its ability to provide quick and easy access to information. With a simple search function, authorised staff members can retrieve the necessary data from various documents within your organisation. This eliminates the need for manual search efforts and empowers your team to find the information they need in seconds.

Deep and factual answers

The intelligent algorithms behind Data Agent enable it to generate deep and factual answers based on your company's data. With the ability to understand the context and semantics of the search query, Data Agent can deliver more than just a keyword match. It provides comprehensive insights by analyzing the data within your documents, giving you a deeper understanding of the information at hand.

Secure and reliable solution

When dealing with company data, security is of utmost importance. Data Agent is designed with robust security measures to ensure the safety of your information. By providing access only to authorised staff members, you can maintain control over who can search and access sensitive data. Additionally, Data Agent's indexing and storage processes are designed to protect the integrity and confidentiality of your documents.

Easy implementation and integration

Implementing Data Agent doesn't have to be a complicated process. Many solutions offer easy integration with existing systems and databases, making it seamless to incorporate into your workflow. With minimal setup and configuration, you can have your Data Agent up and running in no time, ready to streamline your document search processes.

Effortless search across documents

By leveraging the power of Data Agent, you can search across documents effortlessly. Whether your data resides in PDFs, spreadsheets, or other file formats, Data Agent is designed to extract, index, and organise the information in a centralised database. This allows you to search for specific keywords, phrases, or concepts and get accurate results across all your stored documents.

Boosted productivity and efficiency

Having a Data Agent in place can significantly boost productivity and efficiency within your organization. Instead of spending valuable time manually searching through countless documents, your staff members can rely on Data Agent to provide them with accurate information swiftly. This allows your team to focus on critical tasks and make data-driven decisions more efficiently.

Restricted responses to avoid hallucinations

Data Agent is designed to avoid generating hallucinatory or misleading content. It strictly delivers responses based on your organisation's existing data, ensuring the provided information is both factual and relevant, thereby preventing any potential issues.

Perfect for enterprises

Integrating Data Agent into your company's workflow can revolutionize the way you search and access information. By providing quick and easy access, effortless search capabilities, deep and factual answers, and enhanced productivity, Data Agent is an invaluable tool for enterprises with a massive amount of information.

Interested in learning more about Generative AI for your business? Get your free whitepaper on AI and LLMs!

With the rapid advancement of Generative AI and its accessibility to the public, it has become widely popular.

As people recognise AI's impact, the term "AI 2.0" signals a shift towards more versatile models. LLMs like GPT aid professionals in streamlining tasks, restructuring processes, and creating new value for companies and customers.

At Tovie AI, we foresee positive changes in businesses and organisations due to this technological wave.

Our whitepaper dives into GenAI, covering its training, applications, model structures, and industry use cases. Let's explore it together!


AI Revolution 2.0

LLMs + GPT: History, types, and impact on the world around us

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Discover how this technology works

What is RAG?

Retrieval-Augmented Generation (RAG) enhances content creation in enterprise AI applications by combining information retrieval with text generation. It enables AI systems to access organisational data effectively, improving the quality and relevance of generated content

Ways Enterprises can leverage RAG


Develop advanced systems for accurate and contextually relevant responses


Enhance customer interactions with precise and informative responses

Content generation

Assist in creating industry-specific or brand-compliant content

Document summarisation

Efficiently summarise large documents or datasets

Service-agent support

Improve customer interactions with relevant and accurate information

By integrating RAG into their AI solutions, enterprises can optimise knowledge retrieval, boost productivity, and enhance customer experiences

How does RAG work?

RAG initially retrieves important information based on user queries from diverse sources. This information is then utilised by a generator model, typically a large language model (LLM), to produce accurate responses.

Documents and user queries are converted into numerical representations using specialised models to facilitate smooth operation. RAG analyses these numerical representations to enrich user queries with information from the knowledge library. Successful implementation of RAG requires adherence to essential methods for optimal outcomes.

Here are some key best practices for implementing RAG:

  • Select relevant knowledge sources
  • Fine-tune the LLM for domain-specific performance
  • Utilise a retriever model for context extraction
  • Convert data into numerical formats for relevancy searches
  • Regularly update knowledge libraries for the latest information

What to consider when implementing the RAG solution?

When enterprises leverage Retrieval-Augmented Generation (RAG), safety and security are paramount.
Here are key considerations:

Data privacy

Enterprises must safeguard sensitive data in RAG processes to prevent unauthorised access or breaches


Adhering to data protection regulations and industry standards is crucial to maintain compliance while using RAG

Secure integration

Implementing robust security measures to protect data during integration with RAG systems is essential

Access control

Limiting access to RAG tools and data sources to authorised personnel helps prevent misuse or data leaks

Regular Audits

Conducting security audits and assessments regularly can identify vulnerabilities and ensure ongoing protection

By prioritising safety and security measures, enterprises can confidently leverage RAG technology while safeguarding their data and maintaining compliance with regulatory requirements

Adopt new technologies securely

At Tovie AI, we prioritise safety and security when embedding RAG solutions for enterprises. We implement robust data privacy measures and encryption protocols to protect sensitive data and ensure compliance with regulations. Our secure practices include access control mechanisms and regular security audits to identify and address vulnerabilities proactively.

Partnering with Tovie AI guarantees efficient and secure RAG implementations. Our comprehensive data protection approach instils confidence in businesses, allowing them to leverage RAG technology with peace of mind.

Why RAG is important?

RAG tackles significant challenges associated with large language models, such as:

Knowledge Limitations

Large language models (LLMs) have restricted knowledge based on their training data. RAG expands this knowledge by accessing external sources, enabling LLMs to produce more precise and dependable responses

Contextual Constraints

LLMs lack context from private data, leading to inaccuracies when responding to domain-specific queries. RAG provides current world and domain-specific information to enhance GenAI applications' response accuracy

Risk of Hallucinations

LLMs may generate inaccurate or irrelevant responses. RAG mitigates this risk by supplementing LLMs with external knowledge, reducing the occurrence of hallucinations


RAG enables GenAI to reference its sources, enhancing traceability and auditability to track the information used for response generation


What can a Data Agent do?

A Data Agent is an AI solution that swiftly extracts specific information from large datasets. It provides instant, comprehensive responses and simplifies data retrieval, making it user-friendly even without extensive database knowledge. The Data Agent can manage vast and complex datasets, scaling its operations according to the size of the data.

Which business Data Agent is good for?

The Data Agent can be employed by various professionals like business analysts, researchers, marketers, sales, and HR teams, who require efficient data retrieval. It's also beneficial for large corporations handling massive data and SMEs needing effective data management.

Is Data Agent by Tovie AI secure?

Data Agent is designed with a strong emphasis on security, implementing robust encryption and complying with data privacy laws. However, the level of security might differ depending on the bot provider's policies. With Tovie-powered language models, you can expect top-tier privacy and security for your exclusive data. Our priority is safeguarding your data by using Data Masking during AI model training. This method protects sensitive information, upholds data privacy, ensures its integrity, and averts possible security infringements.

Is Data Agent by Tovie AI scalable?

The Data Agent by Tovie AI is scalable. It's designed to handle data of any volume, adjust to increasing loads, and accommodate the growing needs of a business. No matter how much your data expands, the bot ensures efficient and accurate retrieval of information.

Can I use Data Agent commercially?

Yes, you can certainly use Data Agent for commercial purposes. It was expressly created for businesses with the aim to streamline data access, enhance operational efficiency, and provide immediate, comprehensive responses to enterprise data queries, thereby improving overall business productivity.

What is the commercial pricing for the Data Agent?

To learn more about the detailed commercial pricing of Data Agent, please reach out to us at

How to find necessary data at work?

Data Agent can greatly assist in finding relevant information at work. It integrates with multiple data sources within your organisation, allowing you to converse with your data effortlessly and obtain correct responses to complex search scenarios, ensuring quick access to critical information.

Where can I get help?

If you need help with Data Agent, please don't hesitate to reach out to us at We'll be more than happy to assist you.

Does Data Agent provide analytics and chat history?

Yes, Data Agent has a dedicated analytics tab available to all users and provides detailed information on chat history with all created agents.

How do you add Data Agent to the website, app, or system?

Data Agent provides an API that would allow for adding agents to websites, apps, CRMs, etc. There are also a number of channels available out of the box, including Microsoft Teams, Slack and others.

How does Data Agent integrate with Knowledge Bases?

Data Agent can automatically update and train your LLM (Language Learning Model) with documents stored in various platforms, including SharePoint, Confluence, Dropbox, Box, Google Docs, Notion, Microsoft Dynamics 365, and any CRM.

Which messengers are supported by Data Agent?

Data Agent integrates with a wide range of popular communication platforms to streamline your interactions, including Slack, Teams, API, WhatsApp, Viber, Facebook Messenger, Instagram, Telegram, ZenDesk, Vonage, JivoChat, Azure Bot, and SalesForce.

Which language models does Data Agent use?

Data Agent offers Claude Anthropic, Google PaLM, GPT 3.5, GPT 3.5 Turbo, GPT 4, GPT-3.5-turbo-16k, LLaMA (Meta), and on-prem LLMs which are available on request.

Does the Data Agent comply with GDPR?

To fully comply with GDPR guidelines around the use and storage of personal data of EU citizens, we can offer an on-prem-based LLM that is specifically fine-tuned to meet our customers’ business and security needs. For initial testing and or POC/Pilot projects, we recommend using ChatGPT and other public LLMs with no personal data.

Where does the Data Agent store data?

Data used by Data Agent (Tovie AI) is stored in the EU.

How many languages does your solution support?

For models Like ChatGPT, please refer to OpenAI guidelines here:

For on-prem: All major European and Asian languages can be supported.

Does Data Agent support voice? Can a user communicate with an agent with their voice?

Yes, voice is available.

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Thank you for reaching out!

We appreciate you contacting Tovie AI and will get back to you as soon as we can.