Best AI tools for< Investigate Crime Scenes >

Flagright is an AI-native AML compliance and risk management solution designed for EU and UK fintech startups. It offers a comprehensive platform for screening, monitoring, and investigating AML compliance and fraud cases using AI technology. The platform provides real-time transaction monitoring, automated case management, AI forensics for screening, customer risk assessment, and sanctions screening. Flagright also offers integrations, notifications, bad actor database, CRM, KYB & ID verification, and professional services for tailored AML program design and support. Trusted by financial institutions across 6 continents, Flagright is a modern standard for financial crime compliance.

PimEyes is an online face search engine that uses face recognition technology to find pictures containing given faces. It is a great tool to audit copyright infringement, protect your privacy, and find people.

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.

Napier AI is an AI-powered Anti-Money Laundering platform designed to combat evolving threats in the financial industry. It offers a suite of intelligent compliance products that aim to transform organizations' attitudes towards compliance by focusing on efficiency and outcomes. The platform integrates multiple compliance solutions into one master dashboard, provides flexible deployment options, and offers AI-enhanced insights to empower compliance teams to make faster and more accurate decisions. Napier AI is trusted by leading data providers and financial organizations worldwide for its innovative approach to financial crime compliance.

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.

Schwarzthal Tech's Wunderschild is an AI-driven platform for financial crime intelligence that revolutionizes compliance and investigation techniques. It provides intelligence solutions based on network assessment, data linkage, flow aggregation, and machine learning. The platform offers expertise in identifying risks related to Politically Exposed Persons, Serious Organised Crime, Terrorism Financing, and more. Wunderschild's capabilities include compliance enhancement through semi-supervised learning techniques, deep-dive investigations into transnational crime cases, and global companies' beneficiaries network analysis.

Unit21 is a customizable no-code platform designed for risk and compliance operations. It empowers organizations to combat financial crime by providing end-to-end lifecycle risk analysis, fraud prevention, case management, and real-time monitoring solutions. The platform offers features such as AI Copilot for alert prioritization, Ask Your Data for data analysis, Watchlist & Sanctions for ongoing screening, and more. Unit21 focuses on fraud prevention and AML compliance, simplifying operations and accelerating investigations to respond to financial threats effectively and efficiently.

Pascal is an AI-powered risk-based KYC & AML screening and monitoring platform that offers users a faster and more accurate way to assess findings compared to other compliance tools. It leverages AI, machine learning, and Natural Language Processing to analyze open-source and client-specific data, providing insights to identify and assess risks. Pascal simplifies onboarding processes, offers continuous monitoring, reduces false positives, and enables better decision-making through its intuitive interface. It promotes collaboration among different stakeholders and ensures transparency in compliance procedures.

Quantifind is an AI-powered financial crimes automation platform that specializes in Anti-Money Laundering (AML) and Know Your Customer (KYC) solutions. It offers end-to-end automation impact, best-in-class accuracy, and powerful APIs and applications for risk screening, investigations, and compliance in the financial services and public sector industries. Quantifind's Graphyte platform leverages AI and external data to streamline AML-KYC processes, providing comprehensive data coverage, dynamic risk typologies, and seamless integrations with case management systems.

FaceCheck.ID is a facial recognition AI technology-powered search engine that allows users to upload a photo of a person to discover their social media profiles, appearances in blogs, videos, news websites, and more. It helps users verify the authenticity of individuals, avoid dangerous criminals, keep their families safe, and avoid becoming victims of various scams and crimes. The tool is designed to assist in identifying and uncovering information about individuals based on their facial features, with a focus on safety and security.

Hatchet is an AI companion designed to assist on-call engineers in incident response by providing intelligent insights and suggestions based on logs, communications channels, and code analysis. It helps save time and money by automating the triaging and investigation process during critical incidents. The tool is built by engineers with a focus on data security, offering self-hosted deployments, permissions, audit trails, SSO, and version control. Hatchet aims to streamline incident resolution for tier-1 services, enabling faster response and potential problem resolution.

SecureLabs is an AI-powered platform that offers comprehensive security, privacy, and compliance management solutions for businesses. The platform integrates cutting-edge AI technology to provide continuous monitoring, incident response, risk mitigation, and compliance services. SecureLabs helps organizations stay current and compliant with major regulations such as HIPAA, GDPR, CCPA, and more. By leveraging AI agents, SecureLabs offers autonomous aids that tirelessly safeguard accounts, data, and compliance down to the account level. The platform aims to help businesses combat threats in an era of talent shortages while keeping costs down.

Dropzone AI is an award-winning AI application designed to reinforce Security Operations Centers (SOCs) by providing autonomous AI analysts. It replicates the techniques of elite analysts to autonomously investigate alerts, covering various use cases such as phishing, endpoint, network, cloud, identity, and insider threats. The application offers pre-trained AI agents that work alongside human analysts, automating investigation tasks and providing fast, detailed, and accurate reports. With built-in integrations with major security tools, Dropzone AI aims to reduce Mean Time to Respond (MTTR) and allow analysts to focus on addressing real threats.

CrowdStrike is a cloud-based cybersecurity platform that provides endpoint protection, threat intelligence, and incident response services. It uses artificial intelligence (AI) to detect and prevent cyberattacks. CrowdStrike's platform is designed to be scalable and easy to use, and it can be deployed on-premises or in the cloud. CrowdStrike has a global customer base of over 23,000 organizations, including many Fortune 500 companies.

Exabeam is a cybersecurity and compliance platform that offers Security Information and Event Management (SIEM) solutions. The platform provides flexible choices for threat detection, investigation, and response, whether through cloud-based AI-driven solutions or on-premises SIEM deployments. Exabeam's AI-driven Security Operations Platform combines advanced threat detection capabilities with automation to deliver faster and more accurate TDIR. With features like UEBA, SOAR, and insider threat detection, Exabeam helps organizations improve security posture and optimize investments. The platform supports various industries and use cases, offering pre-built content, behavioral analytics, and context enrichment for enhanced threat coverage and compliance.

CensysGPT Beta is a tool that simplifies building queries and empowers users to conduct efficient and effective reconnaissance operations. It enables users to quickly and easily gain insights into hosts on the internet, streamlining the process and allowing for more proactive threat hunting and exposure management.

CrowdStrike is a leading cybersecurity platform that uses artificial intelligence (AI) to protect businesses from cyber threats. The platform provides a unified approach to security, combining endpoint security, identity protection, cloud security, and threat intelligence into a single solution. CrowdStrike's AI-powered technology enables it to detect and respond to threats in real-time, providing businesses with the protection they need to stay secure in the face of evolving threats.

Vectra AI is a leading AI security platform that helps organizations stop advanced cyber attacks by providing an integrated signal for extended detection and response (XDR). The platform arms security analysts with real-time intelligence to detect, prioritize, investigate, and respond to threats across network, identity, cloud, and managed services. Vectra AI's AI-driven detections and Attack Signal Intelligence enable organizations to protect against various attack types and emerging threats, enhancing cyber resilience and reducing risks in critical infrastructure, cloud environments, and remote workforce scenarios. Trusted by over 1100 enterprises worldwide, Vectra AI is recognized for its expertise in AI security and its ability to stop sophisticated attacks that other technologies may miss.

Megagon Labs is an AI research lab focusing on Knowledge Representation & Reasoning, Natural Language Processing, Human-Centered AI, and Data AI Symbiosis. They empower users with better information to make informed decisions through cutting-edge research and technologies. The lab's work includes investigating symbiotic systems, data management for AI, human-centered AI tools, and enhancing NLP capabilities for various domains.

Vectra AI is an advanced AI-driven cybersecurity platform that helps organizations detect, prioritize, investigate, and respond to sophisticated cyber threats in real-time. The platform provides Attack Signal Intelligence to arm security analysts with the necessary intel to stop attacks fast. Vectra AI offers integrated signal for extended detection and response (XDR) across various domains such as network, identity, cloud, and endpoint security. Trusted by 1,500 enterprises worldwide, Vectra AI is known for its patented AI security solutions that deliver the best attack signal intelligence on the planet.

AIDE (Advanced Intrusion Detection Environment) is a tool for monitoring file system changes. It can be used to detect unauthorized changes to monitored files and directories. AIDE was written to be a simple and free alternative to Tripwire. Features currently included in AIDE are as follows: o File attributes monitored: permissions, inode, user, group file size, mtime, atime, ctime, links and growing size. o Checksums and hashes supported: SHA1, MD5, RMD160, and TIGER. CRC32, HAVAL and GOST if Mhash support is compiled in. o Plain text configuration files and database for simplicity. o Rules, variables and macros that can be customized to local site or system policies. o Powerful regular expression support to selectively include or exclude files and directories to be monitored. o gzip database compression if zlib support is compiled in. o Free software licensed under the GNU General Public License v2.

This repository contains the training code of LLM-QAT for large language models. The work investigates quantization-aware training for LLMs, including quantizing weights, activations, and the KV cache. Experiments were conducted on LLaMA models of sizes 7B, 13B, and 30B, at quantization levels down to 4-bits. Significant improvements were observed when quantizing weight, activations, and kv cache to 4-bit, 8-bit, and 4-bit, respectively.

Autonomous agents are designed to achieve specific objectives through self-guided instructions. With the emergence and growth of large language models (LLMs), there is a growing trend in utilizing LLMs as fundamental controllers for these autonomous agents. This repository conducts a comprehensive survey study on the construction, application, and evaluation of LLM-based autonomous agents. It explores essential components of AI agents, application domains in natural sciences, social sciences, and engineering, and evaluation strategies. The survey aims to be a resource for researchers and practitioners in this rapidly evolving field.

HolmesGPT is an open-source DevOps assistant powered by OpenAI or any tool-calling LLM of your choice. It helps in troubleshooting Kubernetes, incident response, ticket management, automated investigation, and runbook automation in plain English. The tool connects to existing observability data, is compliance-friendly, provides transparent results, supports extensible data sources, runbook automation, and integrates with existing workflows. Users can install HolmesGPT using Brew, prebuilt Docker container, Python Poetry, or Docker. The tool requires an API key for functioning and supports OpenAI, Azure AI, and self-hosted LLMs.

PyWhy-LLM is an innovative library that integrates Large Language Models (LLMs) into the causal analysis process, empowering users with knowledge previously only available through domain experts. It seamlessly augments existing causal inference processes by suggesting potential confounders, relationships between variables, backdoor sets, front door sets, IV sets, estimands, critiques of DAGs, latent confounders, and negative controls. By leveraging LLMs and formalizing human-LLM collaboration, PyWhy-LLM aims to enhance causal analysis accessibility and insight.

This repository contains convenience scripts to finetune LLaMa3-8B (or any other foundation model) for chat towards any language (that isn't English). The rationale behind this is that LLaMa3 is trained on primarily English data and while it works to some extent for other languages, its performance is poor compared to English.

MMMU is a benchmark designed to evaluate multimodal models on college-level subject knowledge tasks, covering 30 subjects and 183 subfields with 11.5K questions. It focuses on advanced perception and reasoning with domain-specific knowledge, challenging models to perform tasks akin to those faced by experts. The evaluation of various models highlights substantial challenges, with room for improvement to stimulate the community towards expert artificial general intelligence (AGI).

Beehave is a powerful addon for Godot Engine that enables users to create robust AI systems using behavior trees. It simplifies the design of complex NPC behaviors, challenging boss battles, and other advanced setups. Beehave allows for the creation of highly adaptive AI that responds to changes in the game world and overcomes unexpected obstacles, catering to both beginners and experienced developers. The tool is currently in development for version 3.0.

LLM4EDA is a repository dedicated to showcasing the emerging progress in utilizing Large Language Models for Electronic Design Automation. The repository includes resources, papers, and tools that leverage LLMs to solve problems in EDA. It covers a wide range of applications such as knowledge acquisition, code generation, code analysis, verification, and large circuit models. The goal is to provide a comprehensive understanding of how LLMs can revolutionize the EDA industry by offering innovative solutions and new interaction paradigms.

LLaMa2lang is a repository containing convenience scripts to finetune LLaMa3-8B (or any other foundation model) for chat towards any language that isn't English. The repository aims to improve the performance of LLaMa3 for non-English languages by combining fine-tuning with RAG. Users can translate datasets, extract threads, turn threads into prompts, and finetune models using QLoRA and PEFT. Additionally, the repository supports translation models like OPUS, M2M, MADLAD, and base datasets like OASST1 and OASST2. The process involves loading datasets, translating them, combining checkpoints, and running inference using the newly trained model. The repository also provides benchmarking scripts to choose the right translation model for a target language.

AgentGym is a framework designed to help the AI community evaluate and develop generally-capable Large Language Model-based agents. It features diverse interactive environments and tasks with real-time feedback and concurrency. The platform supports 14 environments across various domains like web navigating, text games, house-holding tasks, digital games, and more. AgentGym includes a trajectory set (AgentTraj) and a benchmark suite (AgentEval) to facilitate agent exploration and evaluation. The framework allows for agent self-evolution beyond existing data, showcasing comparable results to state-of-the-art models.

ControlFlow is a Python framework designed for building agentic AI workflows. It provides a structured approach for defining tasks, assigning specialized AI agents, and orchestrating complex behaviors. By balancing AI autonomy with precise oversight, users can create sophisticated AI-powered applications with confidence. ControlFlow offers a task-centric architecture, structured results with type-safe outputs, specialized agents for efficient problem-solving, ecosystem integration with LangChain models, flexible control over workflows, multi-agent orchestration, and native observability and debugging capabilities.

MathVerse is an all-around visual math benchmark designed to evaluate the capabilities of Multi-modal Large Language Models (MLLMs) in visual math problem-solving. It collects high-quality math problems with diagrams to assess how well MLLMs can understand visual diagrams for mathematical reasoning. The benchmark includes 2,612 problems transformed into six versions each, contributing to 15K test samples. It also introduces a Chain-of-Thought (CoT) Evaluation strategy for fine-grained assessment of output answers.

ResumeFlow is an automated system utilizing Large Language Models (LLMs) to streamline the job application process. It aims to reduce human effort in various steps of job hunting by integrating LLM technology. Users can access ResumeFlow as a web tool, install it as a Python package, or download the source code. The project focuses on leveraging LLMs to automate tasks such as resume generation and refinement, making job applications smoother and more efficient.

This repository provides an LLM-driven audio codec model, LLM-Codec, for building multi-modal LLMs (text and audio modalities). The model enables frozen LLMs to achieve multiple audio tasks in a few-shot style without parameter updates. It compresses the audio modality into a well-trained LLMs token space, treating audio representation as a 'foreign language' that LLMs can learn with minimal examples. The proposed approach supports tasks like speech emotion classification, audio classification, text-to-speech generation, speech enhancement, etc., demonstrating feasibility and effectiveness in simple scenarios. The LLM-Codec model is open-sourced to facilitate research on few-shot audio task learning and multi-modal LLMs.

LLM-Geo is an AI-powered geographic information system (GIS) that leverages Large Language Models (LLMs) for automatic spatial data collection, analysis, and visualization. By adopting LLM as the reasoning core, it addresses spatial problems with self-generating, self-organizing, self-verifying, self-executing, and self-growing capabilities. The tool aims to make spatial analysis easier, faster, and more accessible by reducing manual operation time and delivering accurate results through case studies. It uses GPT-4 API in a Python environment and advocates for further research and development in autonomous GIS.

Felafax is a framework designed to tune LLaMa3.1 on Google Cloud TPUs for cost efficiency and seamless scaling. It provides a Jupyter notebook for continued-training and fine-tuning open source LLMs using XLA runtime. The goal of Felafax is to simplify running AI workloads on non-NVIDIA hardware such as TPUs, AWS Trainium, AMD GPU, and Intel GPU. It supports various models like LLaMa-3.1 JAX Implementation, LLaMa-3/3.1 PyTorch XLA, and Gemma2 Models optimized for Cloud TPUs with full-precision training support.

Knowledge Conflicts for LLMs: A Survey is a repository containing a survey paper that investigates three types of knowledge conflicts: context-memory conflict, inter-context conflict, and intra-memory conflict within Large Language Models (LLMs). The survey reviews the causes, behaviors, and possible solutions to these conflicts, providing a comprehensive analysis of the literature in this area. The repository includes detailed information on the types of conflicts, their causes, behavior analysis, and mitigating solutions, offering insights into how conflicting knowledge affects LLMs and how to address these conflicts.

“Forensic investigator in CSI Miami game, solving crimes with critical thinking.”

Solving cold cases with deep analysis and creating PDF summaries.

You are the Infinite Detective. Enjoy endless guided interactive crime scene investigations

Incarne un détective sur une scène de crime, enquêtes, trouves des indices et deviens le nouveau Sherlock Holmes . 3 Niveaux de difficulté.

Assists in solving cold case crimes with adjustable settings and personalization.

Dives into true crime stories with detailed analysis

Play as a detective to investigate the case and find out the truth.

A detective game simulator, using real-world events and local knowledge to solve a crime mystery..

Access the mind of the world's greatest detective

Detective solving cold cases via net.

I am a detective simulator, inspired by Hercule Poirot.

Your AI Detective for piecing together puzzles and solving any mystery.

Who let the dogs out? Who stole your favorite toy? Who moved my cheese? Let’s find out!

stunspot's advisor for all things Financial Cybersec

一切的骗局在我面前将无所遁形

🔍Dive into unsolvable mysteries with an AI detective at your side. A fascinating tool for mystery enthusiasts, investigators, documentarians, podcasters, writers, and amateur detectives. Use hotkeys for convenience.🔎

🕵‍♂️ Sci-fi robot sleuth exploring mysteriesl

Líder en Latinoamérica en Criminalística, Criminología, Medicina Legal y Forense, e Investigación Criminal

Expert in solving crimes and mysteries, adept at handling extensive data.

Dedicated investigator resolving diverse crimes, ensuring justice and community safety.