Best AI tools for< Federal Agent >

The website provides information on Federal Travel Regulations and guidelines for civil servants and federal employees. It outlines the policies and procedures for official travel, including per diem rates, transportation options, and ethical standards. The site aims to ensure transparency, accountability, and responsible use of government resources by helping users navigate the complexities of federal travel regulations.

FlyFin is the world's #1 A.I. and CPA tax filing service designed for freelancers, self-employed individuals, business owners, and 1099 & W-2 workers. The platform leverages artificial intelligence to identify every possible tax deduction, making tax filing faster, cheaper, and more accurate. With a dedicated team of CPAs, FlyFin ensures precise tax preparation and maximum refunds for its users. The service covers federal and state taxes for various entities, offers full audit insurance, and guarantees a 100% money-back refund policy. FlyFin is a secure and efficient solution for individuals looking to streamline their tax filing process.

Paxton is an advanced AI platform designed to support legal and business professionals by automating and enhancing tasks such as contract review, legal drafting, and document analysis. Utilizing state-of-the-art artificial intelligence, including proprietary Legal Language Models, Paxton streamlines complex legal processes, improves accuracy, and drives efficiency across a wide range of applications.

Vultron Solution is an AI tool designed for Federal Proposal Development, offering unparalleled AI capabilities to compress proposal production timeframes, increase revenue, and enhance proposal quality. The tool utilizes proprietary multi-domain models to deliver unique and high-quality content tailored to each organization's needs. With a focus on security and efficiency, Vultron is trusted by leading government contractors to streamline the proposal development process and drive business growth.

Sweetspot is an AI-powered platform designed for Government Contracting, offering a comprehensive solution to find, manage, and bid on federal, state, local, and education government opportunities. It leverages cutting-edge AI technology to streamline the capture process, from searching for contracts to responding to bids, providing end-to-end support for public sector teams.

ScaDS.AI (Center for Scalable Data Analytics and Artificial Intelligence) is a research center focusing on Data Science, Artificial Intelligence, and Big Data with locations in Dresden and Leipzig. It is one of the five new AI centers in Germany funded under the federal government's AI strategy by the Federal Ministry of Education and Research and the Free State of Saxony. The center collaborates closely with TUD Dresden University of Technology and Leipzig University, aiming to bridge the gap between mass data utilization, knowledge management, and advanced AI methods.

CitizenPortal.ai is an AI tool designed for informed citizens to access a wide range of government-related information and resources. It provides users with the ability to search and browse through various governmental entities and documents, including Congress, Federal Reserve, Supreme Court, NASA, and more. The platform serves as a comprehensive portal for individuals interested in politics and government affairs, offering features such as GPT-based assistance, access to Congressional hearings, executive orders, and the Federalist Papers. CitizenPortal.ai aims to empower users with knowledge and facilitate engagement with the political landscape.

CanTax.ai is an AI-powered platform offering tax help for Canadians. It provides personalized tax advice tailored to individual financial needs, ensuring privacy and security through industry-leading encryption protocols. The platform's artificial intelligence is trained on federal and provincial tax legislation, offering comprehensive knowledge and 24/7 availability for immediate tax advice. CanTax aims to simplify the tax filing process and empower Canadians financially by making expert-level tax guidance accessible to all.

OrangeSlices AI is a platform focused on providing timely, actionable, and responsible information and data products for the competitive marketplace, particularly in the Government Contracting (GovCon) sector. The platform aims to make data available and accessible to organizations of all sizes, assisting Federal government and industry IT and consulting leaders in identifying and engaging with each other effectively. OrangeSlices AI also highlights leaders and companies that excel in their fields, promoting a culture of excellence and innovation.

finagg is a Python package that provides implementations of popular and free financial APIs, tools for aggregating historical data from those APIs into SQL databases, and tools for transforming aggregated data into features useful for analysis and AI/ML. It offers documentation, installation instructions, and basic usage examples for exploring various financial APIs and features. Users can install recommended datasets from 3rd party APIs into a local SQL database, access Bureau of Economic Analysis (BEA) data, Federal Reserve Economic Data (FRED), Securities and Exchange Commission (SEC) filings, and more. The package also allows users to explore raw data features, install refined data features, and perform refined aggregations of raw data. Configuration options for API keys, user agents, and data locations are provided, along with information on dependencies and related projects.

AI4U is a tool that provides a framework for modeling virtual reality and game environments. It offers an alternative approach to modeling Non-Player Characters (NPCs) in Godot Game Engine. AI4U defines an agent living in an environment and interacting with it through sensors and actuators. Sensors provide data to the agent's brain, while actuators send actions from the agent to the environment. The brain processes the sensor data and makes decisions (selects an action by time). AI4U can also be used in other situations, such as modeling environments for artificial intelligence experiments.

hackingBuddyGPT is a framework for testing LLM-based agents for security testing. It aims to create common ground truth by creating common security testbeds and benchmarks, evaluating multiple LLMs and techniques against those, and publishing prototypes and findings as open-source/open-access reports. The initial focus is on evaluating the efficiency of LLMs for Linux privilege escalation attacks, but the framework is being expanded to evaluate the use of LLMs for web penetration-testing and web API testing. hackingBuddyGPT is released as open-source to level the playing field for blue teams against APTs that have access to more sophisticated resources.

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".

The 'awesome-mobile-robotics' repository is a curated list of important content related to Mobile Robotics and AI. It includes resources such as courses, books, datasets, software and libraries, podcasts, conferences, journals, companies and jobs, laboratories and research groups, and miscellaneous resources. The repository covers a wide range of topics in the field of Mobile Robotics and AI, providing valuable information for enthusiasts, researchers, and professionals in the domain.

The 'Awesome AI Guidelines' repository aims to simplify the ecosystem of guidelines, principles, codes of ethics, standards, and regulations around artificial intelligence. It provides a comprehensive collection of resources addressing ethical and societal challenges in AI systems, including high-level frameworks, principles, processes, checklists, interactive tools, industry standards initiatives, online courses, research, and industry newsletters, as well as regulations and policies from various countries. The repository serves as a valuable reference for individuals and teams designing, building, and operating AI systems to navigate the complex landscape of AI ethics and governance.

关于如何编写大语言模型的prompt的一系列课

AixLib is a Modelica model library for building performance simulations developed at RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate (EBC) in Aachen, Germany. It contains models of HVAC systems as well as high and reduced order building models. The name AixLib is derived from the city's French name Aix-la-Chapelle, following a local tradition. The library is continuously improved and offers citable papers for reference. Contributions to the development can be made via Issues section or Pull Requests, following the workflow described in the Wiki. AixLib is released under a 3-clause BSD-license with acknowledgements to public funded projects and financial support by BMWi (German Federal Ministry for Economic Affairs and Energy).

CISO Assistant is a tool that helps organizations manage their cybersecurity posture and compliance. It provides a centralized platform for managing security controls, threats, and risks. CISO Assistant also includes a library of pre-built frameworks and tools to help organizations quickly and easily implement best practices.

Kaapana is an open-source toolkit for state-of-the-art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. Obtaining large amounts of medical data necessary for developing and training modern machine learning methods is an extremely challenging effort that often fails in a multi-center setting, e.g. due to technical, organizational and legal hurdles. A federated approach where the data remains under the authority of the individual institutions and is only processed on-site is, in contrast, a promising approach ideally suited to overcome these difficulties. Following this federated concept, the goal of Kaapana is to provide a framework and a set of tools for sharing data processing algorithms, for standardized workflow design and execution as well as for performing distributed method development. This will facilitate data analysis in a compliant way enabling researchers and clinicians to perform large-scale multi-center studies. By adhering to established standards and by adopting widely used open technologies for private cloud development and containerized data processing, Kaapana integrates seamlessly with the existing clinical IT infrastructure, such as the Picture Archiving and Communication System (PACS), and ensures modularity and easy extensibility.

ExplainableAI.jl is a Julia package that implements interpretability methods for black-box classifiers, focusing on local explanations and attribution maps in input space. The package requires models to be differentiable with Zygote.jl. It is similar to Captum and Zennit for PyTorch and iNNvestigate for Keras models. Users can analyze and visualize explanations for model predictions, with support for different XAI methods and customization. The package aims to provide transparency and insights into model decision-making processes, making it a valuable tool for understanding and validating machine learning models.

AIW is a code base for experiments and raw data related to Alice in Wonderland, showcasing complete reasoning breakdown in state-of-the-art large language models. Users can collect experiments data using LiteLLM and TogetherAI, and plot the data using provided scripts. The tool allows for executing experiments over LiteLLM and lmsys, with options for different prompt types and AIW variations. The project also includes acknowledgments and a citation for reference.

AI assistant for U.S. Federal Rules, providing precise answers with citations.

Personnel Management Expert to the Federal Government

Especialista em análise de projetos de lei para comissões do Senado Federal

Identify and Confirm Interior Signage Code Details & Requirements. Federal, California ADA Signage Codes (NY Coming Soon)

Your go-to source for Canadian legal frameworks, now with federal property insights!

Especialista em leis brasileiras. Tenho conhecimentos detalhados da constituição federal, código penal, código de defesa do consumidor, código de trânsito e lei do inquilinato. Esta ferramenta não substitui aconselhamento jurídico profissional.

An assistant for inquiries about the U.S. SBIR and STTR programs.