Best AI tools for< Accelerate Due Diligence >

8VDX is an AI application that offers fine-tuned AI models for credit funds, empowering users to make data-driven decisions in the realm of credit investing. The platform enhances speed, accuracy, and strategic depth across various financial instruments like bonds, private credit, and CLOs. By leveraging AI technology, 8VDX streamlines the investment analysis process, automates bond screening, and provides continuous learning from surveillance to optimize investment strategies.

Kira Systems is a machine learning contract search, review, and analysis software that helps businesses identify, extract, and analyze content in their contracts and documents. It uses patented machine learning technology to extract concepts and data points with high efficiency and accuracy. Kira also has built-in intelligence that streamlines the contract review process with out-of-the-box smart fields. Businesses can also create their own smart fields to find specific data points using Kira's no-code machine learning tool. Kira's adaptive workflows allow businesses to organize, track, and export results. Kira has a partner ecosystem that allows businesses to transform how teams work with their contracts.

SymphonyAI offers AI SaaS solutions for financial crime prevention, helping organizations detect fraud, conduct customer due diligence, and prevent payment fraud. Their solutions leverage generative and predictive AI to enhance efficiency and effectiveness in investigating financial crimes. SymphonyAI's products cater to industries like banking, insurance, financial markets, and private banking, providing rapid deployment, scalability, and seamless integration to meet regulatory compliance requirements.

SymphonyAI NetReveal Financial Services is an AI-powered platform that offers solutions for financial crime prevention in various industries such as banking, insurance, financial markets, and private banking. The platform utilizes predictive and generative AI applications to enhance efficiency, reduce fraud, streamline compliance, and maximize output. SymphonyAI provides a fundamentally different approach to AI by combining high-value AI capabilities with industry-leading predictive and generative AI technologies. The platform offers a range of solutions including transaction monitoring, customer due diligence, payment fraud detection, and enterprise investigation management. SymphonyAI aims to revolutionize financial crime prevention by leveraging AI to detect suspicious activity, expedite investigations, and improve compliance operations.

ZBrain is an enterprise generative AI platform that offers a suite of AI-based tools and solutions for various industries. It provides real-time insights, executive summaries, due diligence enhancements, and customer support automation. ZBrain empowers businesses to streamline workflows, optimize processes, and make data-driven decisions. With features like seamless integration, no-code business logic, continuous improvement, multiple data integrations, extended DB, advanced knowledge base, and secure data handling, ZBrain aims to enhance operational efficiency and productivity across organizations.

Orbital Insight is a leading geospatial data analytics platform that provides users with the ability to query the world with three basic parameters: WHAT type of activity? WHERE on earth? WHEN? The platform automates the most difficult steps of deriving insights, allowing you to answer many challenging geospatial questions. Orbital Insight's GO platform is designed for enterprise collaboration and transforms multiple geospatial data sources to accelerate and streamline team member's research, reporting, due diligence, and more.

Adjust is an AI-driven platform that helps mobile app developers accelerate their app's growth through a comprehensive suite of measurement, analytics, automation, and fraud prevention tools. The platform offers unlimited measurement capabilities across various platforms, powerful analytics and reporting features, AI-driven decision-making recommendations, streamlined operations through automation, and data protection against mobile ad fraud. Adjust also provides solutions for iOS and SKAdNetwork success, CTV and OTT performance enhancement, ROI measurement, fraud prevention, and incrementality analysis. With a focus on privacy and security, Adjust empowers app developers to optimize their marketing strategies and drive tangible growth.

Tidio is an AI-powered customer service solution that helps businesses automate support, convert more leads, and increase revenue. With Lyro AI Chatbot, businesses can answer up to 70% of customer inquiries without human intervention, freeing up support agents to focus on high-value requests. Tidio also offers live chat, helpdesk, and automation features to help businesses provide excellent customer support and grow their business.

Tidio is an AI-powered customer service solution that helps businesses automate their support and sales processes. With Lyro AI Chatbot, businesses can solve up to 70% of customer problems without human intervention. Tidio also offers live chat, helpdesk, and automation features to help businesses provide excellent customer service and grow their revenue.

HubSpot is an AI-powered platform that offers CRM, marketing, sales, customer service, and content management tools. It provides a unified platform optimized by AI, with features such as marketing automation, sales pipeline development, customer support, content creation, and data organization. HubSpot caters to businesses of all sizes, from startups to large enterprises, helping them generate leads, automate processes, and improve customer retention. The platform also offers a range of integrations and solutions tailored to different business needs.

EarnBetter is an AI-powered platform that offers assistance in creating professional resumes, cover letters, and job search support. The platform utilizes artificial intelligence to rewrite and reformat resumes, generate tailored cover letters, provide personalized job matches, and offer interview support. Users can upload their current resume to get started and access a range of features to enhance their job search process. EarnBetter aims to streamline the job search experience by providing free, unlimited, and professional document creation services.

Gab AI is an uncensored and unfiltered AI platform that offers a wide range of AI tools and applications. It provides users with access to various AI characters, chatbots, image generators, and creative writing prompts. The platform aims to accelerate users' creativity and knowledge by engaging them in conversations, generating content, and exploring different AI-generated outputs.

Sense Talent Engagement Platform is an AI-powered recruitment platform that offers a comprehensive suite of tools to streamline the hiring process. It provides automation workflows, database cleanup, interview scheduling, text messaging, mass texting, WhatsApp and SMS integration, mobile app support, candidate matching, AI chatbot, job matching, scheduling bot, smart FAQ, pre-screening, sourcing, live chat, instant apply, talent CRM, generative AI, voice AI, referrals, analytics, and more. The platform caters to various industries such as financial services, healthcare, logistics, manufacturing, retail, staffing, technology, and more, helping organizations attract, engage, and retain top talent efficiently.

Tabnine is an AI code assistant that accelerates and simplifies software development while keeping your code private, secure, and compliant. It streamlines code generation, automates mundane tasks, and provides context-aware coding assistance. Tabnine offers total code privacy with zero data retention, complete protection from IP issues, and is trusted by millions of developers and thousands of companies. It is highly personalized, supports popular languages and IDEs, and offers industry-leading AI code generation.

Builder.io is an AI-powered visual development platform that accelerates digital teams by providing design-to-code solutions. With Visual Copilot, users can transform Figma designs into production-ready code quickly and efficiently. The platform offers features like AI-powered design-to-code conversion, visual editing, and enterprise CMS integration. Builder.io enables users to streamline their development process and bring ideas to production in seconds.

Rayyan is an intelligent systematic review tool trusted by over 500,000 researchers worldwide. It helps users organize, manage, and accelerate collaborative systematic literature reviews. Rayyan empowers users to work remotely and collaborate with distributed research teams, offering membership packages with onboarding, training, and priority support. The tool is designed to understand language, learn from user decisions, and facilitate quick navigation through systematic reviews. Rayyan also provides solutions for organizations and businesses to streamline research processes and save valuable researcher time.

Katalon is a modern, comprehensive quality management platform that helps teams of any size deliver the highest quality digital experiences. It offers a range of features including test authoring, test management, test execution, reporting & analytics, and AI-powered testing. Katalon is suitable for testers of all backgrounds, providing a single platform for testing web, mobile, API, desktop, and packaged apps. With AI capabilities, Katalon simplifies test automation, streamlines testing operations, and scales testing programs for enterprise teams.

Scale AI is an AI tool that accelerates the development of AI applications for enterprise, government, and automotive sectors. It offers Scale Data Engine for generative AI, Scale GenAI Platform, and evaluation services for model developers. The platform leverages enterprise data to build sustainable AI programs and partners with leading AI models. Scale's focus on generative AI applications, data labeling, and model evaluation sets it apart in the AI industry.

Patsnap is an AI-powered innovation intelligence platform that provides data, analytics, and expertise for innovative companies. It revolutionizes how IP and R&D teams collaborate by helping them analyze the competitive landscape, reduce risks, and accelerate the entire innovation lifecycle. Patsnap offers a connected product suite trusted by over 12,000 innovators worldwide, saving valuable time and resources. The platform enables users to ideate, validate, review, submit, and monitor innovations with advanced AI tools and collaboration features.

Tricentis is an AI-powered testing tool that offers a comprehensive set of test automation capabilities to address various testing challenges. It provides end-to-end test automation solutions for a wide range of applications, including Salesforce, mobile testing, performance testing, and data integrity testing. Tricentis leverages advanced ML technologies to enable faster and smarter testing, ensuring quality at speed with reduced risk, time, and costs. The platform also offers continuous performance testing, change and data intelligence, and model-based, codeless test automation for mobile applications.

Awesome Algorand is a curated list of resources related to the Algorand Blockchain, including official resources, wallets, blockchain explorers, portfolio trackers, learning resources, development tools, DeFi platforms, nodes & consensus participation, subscription management, security auditing services, blockchain bridges, oracles, name services, community resources, Algorand Request for Comments, metrics and analytics services, decentralized voting tools, and NFT marketplaces. The repository provides a comprehensive collection of tools, tutorials, protocols, and platforms for developers, users, and enthusiasts interested in the Algorand ecosystem.

Embedded inference of Deep Learning models is quite challenging due to high compute requirements. TI’s Edge AI software product helps optimize and accelerate inference on TI’s embedded devices. It supports heterogeneous execution of DNNs across cortex-A based MPUs, TI’s latest generation C7x DSP, and DNN accelerator (MMA). The solution simplifies the product life cycle of DNN development and deployment by providing a rich set of tools and optimized libraries.

TriForce is a training-free tool designed to accelerate long sequence generation. It supports long-context Llama models and offers both on-chip and offloading capabilities. Users can achieve a 2.2x speedup on a single A100 GPU. TriForce also provides options for offloading with tensor parallelism or without it, catering to different hardware configurations. The tool includes a baseline for comparison and is optimized for performance on RTX 4090 GPUs. Users can cite the associated paper if they find TriForce useful for their projects.

MInference is a tool designed to accelerate pre-filling for long-context Language Models (LLMs) by leveraging dynamic sparse attention. It achieves up to a 10x speedup for pre-filling on an A100 while maintaining accuracy. The tool supports various decoding LLMs, including LLaMA-style models and Phi models, and provides custom kernels for attention computation. MInference is useful for researchers and developers working with large-scale language models who aim to improve efficiency without compromising accuracy.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

AI-Drug-Discovery-Design is a repository focused on Artificial Intelligence-assisted Drug Discovery and Design. It explores the use of AI technology to accelerate and optimize the drug development process. The advantages of AI in drug design include speeding up research cycles, improving accuracy through data-driven models, reducing costs by minimizing experimental redundancies, and enabling personalized drug design for specific patients or disease characteristics.

KULLM (구름) is a Korean Large Language Model developed by Korea University NLP & AI Lab and HIAI Research Institute. It is based on the upstage/SOLAR-10.7B-v1.0 model and has been fine-tuned for instruction. The model has been trained on 8×A100 GPUs and is capable of generating responses in Korean language. KULLM exhibits hallucination and repetition phenomena due to its decoding strategy. Users should be cautious as the model may produce inaccurate or harmful results. Performance may vary in benchmarks without a fixed system prompt.

The Enterprise Azure OpenAI Hub is a comprehensive repository designed to guide users through the world of Generative AI on the Azure platform. It offers a structured learning experience to accelerate the transition from concept to production in an Enterprise context. The hub empowers users to explore various use cases with Azure services, ensuring security and compliance. It provides real-world examples and playbooks for practical insights into solving complex problems and developing cutting-edge AI solutions. The repository also serves as a library of proven patterns, aligning with industry standards and promoting best practices for secure and compliant AI development.

Data-to-paper is an AI-driven framework designed to guide users through the process of conducting end-to-end scientific research, starting from raw data to the creation of comprehensive and human-verifiable research papers. The framework leverages a combination of LLM and rule-based agents to assist in tasks such as hypothesis generation, literature search, data analysis, result interpretation, and paper writing. It aims to accelerate research while maintaining key scientific values like transparency, traceability, and verifiability. The framework is field-agnostic, supports both open-goal and fixed-goal research, creates data-chained manuscripts, involves human-in-the-loop interaction, and allows for transparent replay of the research process.

The Machine Learning Road Map is a comprehensive guide designed to take individuals from various levels of machine learning knowledge to a basic understanding of machine learning principles using high-quality, free resources. It aims to simplify the complex and rapidly growing field of machine learning by providing a structured roadmap for learning. The guide emphasizes the importance of understanding AI for everyone, the need for patience in learning machine learning due to its complexity, and the value of learning from experts in the field. It covers five different paths to learning about machine learning, catering to consumers, aspiring AI researchers, ML engineers, developers interested in building ML applications, and companies looking to implement AI solutions.

PEFT (Parameter-Efficient Fine-Tuning) is a collection of state-of-the-art methods that enable efficient adaptation of large pretrained models to various downstream applications. By only fine-tuning a small number of extra model parameters instead of all the model's parameters, PEFT significantly decreases the computational and storage costs while achieving performance comparable to fully fine-tuned models.

InfLLM is a training-free memory-based method that unveils the intrinsic ability of LLMs to process streaming long sequences. It stores distant contexts into additional memory units and employs an efficient mechanism to lookup token-relevant units for attention computation. Thereby, InfLLM allows LLMs to efficiently process long sequences while maintaining the ability to capture long-distance dependencies. Without any training, InfLLM enables LLMs pre-trained on sequences of a few thousand tokens to achieve superior performance than competitive baselines continually training these LLMs on long sequences. Even when the sequence length is scaled to 1, 024K, InfLLM still effectively captures long-distance dependencies.

Laragenie is an AI chatbot designed to understand and assist developers with their codebases. It runs on the command line from a Laravel app, helping developers onboard to new projects, understand codebases, and provide daily support. Laragenie accelerates workflow and collaboration by indexing files and directories, allowing users to ask questions and receive AI-generated responses. It supports OpenAI and Pinecone for processing and indexing data, making it a versatile tool for any repo in any language.

The Radicalbit AI Monitoring Platform provides a comprehensive solution for monitoring Machine Learning and Large Language models in production. It helps proactively identify and address potential performance issues by analyzing data quality, model quality, and model drift. The repository contains files and projects for running the platform, including UI, API, SDK, and Spark components. Installation using Docker compose is provided, allowing deployment with a K3s cluster and interaction with a k9s container. The platform documentation includes a step-by-step guide for installation and creating dashboards. Community engagement is encouraged through a Discord server. The roadmap includes adding functionalities for batch and real-time workloads, covering various model types and tasks.

LitData is a tool designed for blazingly fast, distributed streaming of training data from any cloud storage. It allows users to transform and optimize data in cloud storage environments efficiently and intuitively, supporting various data types like images, text, video, audio, geo-spatial, and multimodal data. LitData integrates smoothly with frameworks such as LitGPT and PyTorch, enabling seamless streaming of data to multiple machines. Key features include multi-GPU/multi-node support, easy data mixing, pause & resume functionality, support for profiling, memory footprint reduction, cache size configuration, and on-prem optimizations. The tool also provides benchmarks for measuring streaming speed and conversion efficiency, along with runnable templates for different data types. LitData enables infinite cloud data processing by utilizing the Lightning.ai platform to scale data processing with optimized machines.

T-MAC is a kernel library that directly supports mixed-precision matrix multiplication without the need for dequantization by utilizing lookup tables. It aims to boost low-bit LLM inference on CPUs by offering support for various low-bit models. T-MAC achieves significant speedup compared to SOTA CPU low-bit framework (llama.cpp) and can even perform well on lower-end devices like Raspberry Pi 5. The tool demonstrates superior performance over existing low-bit GEMM kernels on CPU, reduces power consumption, and provides energy savings. It achieves comparable performance to CUDA GPU on certain tasks while delivering considerable power and energy savings. T-MAC's method involves using lookup tables to support mpGEMM and employs key techniques like precomputing partial sums, shift and accumulate operations, and utilizing tbl/pshuf instructions for fast table lookup.

Home LLM is a project that provides the necessary components to control your Home Assistant installation with a completely local Large Language Model acting as a personal assistant. The goal is to provide a drop-in solution to be used as a "conversation agent" component by Home Assistant. The 2 main pieces of this solution are Home LLM and Llama Conversation. Home LLM is a fine-tuning of the Phi model series from Microsoft and the StableLM model series from StabilityAI. The model is able to control devices in the user's house as well as perform basic question and answering. The fine-tuning dataset is a custom synthetic dataset designed to teach the model function calling based on the device information in the context. Llama Conversation is a custom component that exposes the locally running LLM as a "conversation agent" in Home Assistant. This component can be interacted with in a few ways: using a chat interface, integrating with Speech-to-Text and Text-to-Speech addons, or running the oobabooga/text-generation-webui project to provide access to the LLM via an API interface.

Demucs GUI is a graphical user interface for the music separation project Demucs. It aims to allow users without coding experience to easily separate tracks. The tool provides a user-friendly interface for running the Demucs project, which originally used the scientific library torch. The GUI simplifies the process of separating tracks and provides support for different platforms such as Windows, macOS, and Linux. Users can donate to support the development of new models for the project, and the tool has specific system requirements including minimum system versions and hardware specifications.

DashInfer is a C++ runtime tool designed to deliver production-level implementations highly optimized for various hardware architectures, including x86 and ARMv9. It supports Continuous Batching and NUMA-Aware capabilities for CPU, and can fully utilize modern server-grade CPUs to host large language models (LLMs) up to 14B in size. With lightweight architecture, high precision, support for mainstream open-source LLMs, post-training quantization, optimized computation kernels, NUMA-aware design, and multi-language API interfaces, DashInfer provides a versatile solution for efficient inference tasks. It supports x86 CPUs with AVX2 instruction set and ARMv9 CPUs with SVE instruction set, along with various data types like FP32, BF16, and InstantQuant. DashInfer also offers single-NUMA and multi-NUMA architectures for model inference, with detailed performance tests and inference accuracy evaluations available. The tool is supported on mainstream Linux server operating systems and provides documentation and examples for easy integration and usage.

Accelerate web app development with Material Tailwind GPT's components - 10x faster.

Accelerates the learning of key phrases and cultural norms for travelers in various languages.

Expert in tailored accelerator search for startups.

The Go-To Coach for Aspiring Digital Entrepreneurs, Innovators, & Startups. Learn More at UnderdogInnovationInc.com.

Niche-focused startup guide, humorous, strategic, simplifying ideas.

Drop in any requirements or any text ; I'll help you create an MVP with insights.

A guide for developing university-focused digital startup accelerator programs.