Document Upload

Upload documents to extract and utilize contextually relevant information. Reduce model hallucinations and provide precise, tailored responses with citations.

Document upload enabled employees to upload relevant documents and leverage AI models to extract and utilize contextually relevant information.

This process significantly reduces model hallucinations and provides precise, tailored responses with citations specific to the uploaded documents. The AI model then searches these documents, retrieves relevant examples, and cites them directly to provide detailed and accurate responses. Our framework also includes options for creating organized document collections, enabling more focused searches.

In our example, we demonstrate how a proposal writer could upload technical past performance documents and use the chat interface to generate accurate summaries that can be used in future proposals. This method can be adapted to various documents and fields, streamlining operations and improving efficiency. To learn more, explore additional videos or book a software demo directly with us

Custom Prompts

Create reusable prompts to set tone, provide context, or define personas, tailoring model responses to your needs. Share across teams for consistent LLM usage.

Custom prompts in SecureGPT allow users to define specific guidelines and context for their interactions with AI. By adjusting the system prompt, you can tailor responses to suit particular tasks, personas, or industries, ensuring precise and relevant outputs every time.

This feature is designed to adapt to a wide range of needs. For instance, you could create a prompt for drafting formal government contracts, generating creative marketing copy, or even summarizing dense technical documents. SecureGPT makes it easy to save and reuse these prompts, saving time and ensuring consistency across tasks.

To use custom prompts, simply navigate to the prompts workspace, create a new prompt, and define its parameters. Once saved, these prompts can be accessed using a simple command within the chat interface. With this intuitive setup, users can seamlessly toggle between different use cases, whether crafting content, summarizing data, or collaborating on specialized projects.

Side-by-Side Multi-Model Prompting

Prompt two different models at the same time side by side. Pick either your favorite output or use the combination of the two to produce high quality outputs.

SecureGPT offers an exciting feature: side-by-side or multi-model prompting, which allows users to work with multiple AI models at the same time. This capability is not commonly found in most other LLM interfaces and enables users to compare outputs directly.

By clicking a simple plus button, users can select two models—like GPT-4o and Claude sonnet from a drop-down menu and run them in parallel. For instance, users could prompt both models to: "write a blog post on why the F35 program is considered a failure." This setup shows both outputs side-by-side, making it easier to identify the strengths and weaknesses of each model.

A standout feature of SecureGPT is the ability to then merge these two outputs together. By merging responses, users can combine the best aspects of both models into a single, cohesive result, often achieving much more aligned and robust outcomes tailored to their needs.

This unique functionality has been widely praised, as it empowers users to get creative, make informed comparisons, and produce optimized outputs effortlessly, all from a user-friendly and intuitive interface.

Agents & Code Execution

With SecureGPT, your team can execute code and access real-time data. This enables your team to use the latest data in their responses and allows non-technical team members to automate workflows using code effortlessly.

Large language models, like ChatGPT 4.0, are trained on datasets that might be months or even years old. This means they can't access real-time data unless explicitly programmed to. SecureGPT solves this limitation by enabling Python code execution, allowing LLMs to fetch and use real-time data in responses.

For example, if a user asks for the current weather in a location or the precise time in a specific timezone, SecureGPT can execute code to call APIs, retrieve the latest information, and incorporate it seamlessly into the conversation. This represents a significant leap beyond static, training-data-only models.

Beyond real-time information retrieval, SecureGPT also enables non-technical users to perform complex workflows. A technical expert can write code once, such as generating a daily report or processing specific data. A non-technical user can then reuse this functionality by simply interacting with the model in plain language, without needing to write or understand the underlying code.

This feature has proven invaluable for corporate applications, where teams can automate repetitive tasks and access up-to-date data, all while staying within an accessible and user-friendly environment. This unlocks greater efficiency, creativity, and technical possibilities for a wide range of users.

SecureGPT Training and Support for Your Team

Our team is here to help your business get the most out of SecureGPT. We focus on improving your team's productivity and making sure you're fully equipped to use our tools effectively.

For larger organizations, we offer training programs and support to help roll out AI models across your teams. This includes onboarding, custom data setups, team-specific training, and reporting to fit your goals. We’ll work with you every step of the way to ensure SecureGPT works seamlessly for your entire organization.