Best AI tools for< Process Json >
20 - AI tool Sites
Auto Localize
The website offers an AI Localization tool for Xcode and App Store Connect, aiming to simplify the localization process for developers. It provides features such as instant localization for Xcode projects, seamless App Store Connect integration, and high-quality translations powered by OpenAI's ChatGPT models. The tool supports various platforms like Java, Android Studio, Flutter, .NET, and Unity projects, making it a versatile solution for app localization.
BuildShip
BuildShip is a batch processing tool for ChatGPT that allows users to process ChatGPT tasks in parallel on a spreadsheet UI with CSV/JSON import and export. It supports various OpenAI models, including GPT4, Claude 3, and Gemini. Users can start with readymade templates and customize them with their own logic and models. The data generated is stored securely on the user's own Google Cloud project, and team collaboration is supported with granular access control.
Isomeric
Isomeric is an AI tool that uses artificial intelligence to semantically understand unstructured text and extract specific data. It transforms messy text into machine-readable JSON, enabling users to extract insights, process data, and deliver results efficiently. From web scraping to browser extensions and general information extraction, Isomeric helps users scale their data gathering pipeline in seconds. The tool is designed to help users pull key data from various sources like websites, transcripts, legal documents, and more, and returns structured output following the common JSON Schema spec. Isomeric is widely used in customer support platforms, data orchestration platforms, legal services, and more to automate data extraction and analysis.
PDFMerse
PDFMerse is an AI-powered data extraction tool that revolutionizes how users handle document data. It allows users to effortlessly extract information from PDFs with precision, saving time and enhancing workflow. With cutting-edge AI technology, PDFMerse automates data extraction, ensures data accuracy, and offers versatile output formats like CSV, JSON, and Excel. The tool is designed to dramatically reduce processing time and operational costs, enabling users to focus on higher-value tasks.
Fleak AI Workflows
Fleak AI Workflows is a low-code serverless API Builder designed for data teams to effortlessly integrate, consolidate, and scale their data workflows. It simplifies the process of creating, connecting, and deploying workflows in minutes, offering intuitive tools to handle data transformations and integrate AI models seamlessly. Fleak enables users to publish, manage, and monitor APIs effortlessly, without the need for infrastructure requirements. It supports various data types like JSON, SQL, CSV, and Plain Text, and allows integration with large language models, databases, and modern storage technologies.
Tablize
Tablize is a powerful data extraction tool that helps you turn unstructured data into structured, tabular format. With Tablize, you can easily extract data from PDFs, images, and websites, and export it to Excel, CSV, or JSON. Tablize uses artificial intelligence to automate the data extraction process, making it fast and easy to get the data you need.
Process Street
Process Street is an AI-powered platform that helps businesses streamline their processes and improve operational efficiency. It offers features such as workflows automation, data unification, document sharing, and AI transformation. With Process Street, users can create, track, and complete tasks efficiently, make data-driven decisions, and automate repetitive tasks using generative AI. The platform also provides analytics to track key performance indicators and ensure consistent adherence to procedures. Process Street is trusted by top companies to revolutionize workflow management and drive productivity and growth.
Process Street
Process Street is a powerful checklist, workflow, and SOP software that is designed to streamline and automate business processes. It offers a wide range of features such as workflows, projects, data sets, forms, and pages to help organizations organize and manage their operations efficiently. With AI capabilities, Process Street can transform manual processes, boost productivity, and empower decision-making with analytics. The platform also provides integrations with various tools for maximum efficiency.
super.AI
Super.AI provides Intelligent Document Processing (IDP) solutions powered by Large Language Models (LLMs) and human-in-the-loop (HITL) capabilities. It automates document processing tasks such as data extraction, classification, and redaction, enabling businesses to streamline their workflows and improve accuracy. Super.AI's platform leverages cutting-edge AI models from providers like Amazon, Google, and OpenAI to handle complex documents, ensuring high-quality outputs. With its focus on accuracy, flexibility, and scalability, Super.AI caters to various industries, including financial services, insurance, logistics, and healthcare.
Smace
Smace is an AI-powered SaaS platform designed to enhance process implementation efficiency. It offers features such as enhanced process collaboration, automated workflows and integration, streamlined task management, and data-driven decision support. Smace aims to bridge the gap between process design and execution, promoting team efficiency, streamlined collaboration, and advanced integration.
Greenhouse
Greenhouse is an AI-powered applicant tracking software and hiring platform that offers smart hiring tools to streamline the hiring process. It provides features such as AI tools for sourcing, texting solutions, and feature upgrades to help connect teams and propel success. Greenhouse is designed to help companies hire fairly and purposefully, offering expertise and advice to maximize hiring ROI and support business growth at any stage.
Expertia AI
Expertia AI is an AI-powered hiring partner that leverages advanced algorithms and machine learning to streamline the recruitment process. It offers a comprehensive suite of tools to assist HR professionals in sourcing, screening, and selecting top talent efficiently. By automating repetitive tasks and providing data-driven insights, Expertia AI helps companies make informed hiring decisions and improve overall recruitment outcomes.
PyjamaHR
PyjamaHR is a leading AI-powered Applicant Tracking System (ATS) and recruitment software designed to streamline the hiring process for businesses of all sizes. It offers advanced features such as source management, candidate evaluation, collaboration tools, and AI-powered candidate tests to enhance the efficiency and effectiveness of the recruitment process. With a user-friendly interface and robust security measures, PyjamaHR is a trusted solution for managing talent acquisition and improving hiring outcomes.
Recooty
Recooty is a modern applicant tracking system designed for growing companies to streamline their recruiting process. It offers features such as applicant tracking, job posting, candidate tracking, interview scheduling, talent pool management, employer branding, and HR tools. With Recooty, companies can attract, engage, and hire their next teammates with ease. The platform also provides resources like job descriptions, templates, interview questions, and AI tools to enhance the recruitment experience.
MyEssayWriter.ai
MyEssayWriter.ai is an AI-powered essay writing tool that offers advanced features to help students generate high-quality essays efficiently. The tool is designed to save time, improve writing skills, and provide unique and plagiarism-free content. With a user-friendly interface and customizable essays, MyEssayWriter.ai aims to revolutionize the writing process for students worldwide.
La Growth Machine
La Growth Machine is a multichannel sales automation tool that helps users import and enrich leads, automate conversions, manage leads, and analyze performances. It offers features such as LinkedIn Voice Messages, multichannel inbox, calls, automation of actions and messages, AI-powered writing assistance, campaign analysis, lead management, and more. La Growth Machine streamlines operational processes, enhances performance, and centralizes data in one place. With a focus on multi-channel prospecting, the tool aims to increase conversations and opportunities for users. Trusted by over 10,000 professionals, La Growth Machine provides a seamless experience for reaching out to leads across various platforms.
myInterview
myInterview is an AI tool designed for intelligent candidate video screening. It utilizes artificial intelligence to streamline the recruitment process by analyzing video interviews. The tool helps employers efficiently evaluate candidates' communication skills, personality traits, and overall suitability for the job role. With myInterview, organizations can save time and resources typically spent on traditional screening methods, leading to faster hiring decisions and improved candidate experience.
hireEZ
hireEZ is a Sourcing and Recruitment CRM for Talent Acquisition Platform that leverages AI technology to streamline the recruitment process. It offers features such as AI Sourcing, Applicant Match, Automated Outreach, Intelligent Talent Pools, and Insights & Analytics. The platform aims to enhance candidate experience, improve recruitment efficiency, and empower data-driven recruiting strategies for businesses across various industries.
ContentBot
ContentBot is an AI content automation tool that offers a suite of automation tools to streamline content creation processes. It provides features such as AI Blog Writer, AI Flows, Importer, and Humanizer to help users generate high-quality content efficiently. ContentBot supports over 110 languages and uses AI models like GPT-4 by OpenAI to create unique and original content. The tool caters to various content creators, including digital marketers, content marketers, founders, copywriters, SEO specialists, and bloggers, by offering a range of content creation solutions.
Scratchpad
Scratchpad is an AI-powered workspace designed for sales teams to streamline their sales processes and enhance productivity. It offers features such as AI Sales Assistant, Pipeline Management, Slack Deal Rooms, Automations & Enablement, Deal Inspection, and Sales Forecasting. With Scratchpad, sales teams can automate collaboration, improve Salesforce hygiene, track deal progress, and gain insights into deal movement and pipeline changes. The application aims to simplify sales workflows, provide real-time notes and call summaries, and enhance team collaboration for better performance and efficiency.
20 - Open Source AI Tools
json_repair
This simple package can be used to fix an invalid json string. To know all cases in which this package will work, check out the unit test. Inspired by https://github.com/josdejong/jsonrepair Motivation Some LLMs are a bit iffy when it comes to returning well formed JSON data, sometimes they skip a parentheses and sometimes they add some words in it, because that's what an LLM does. Luckily, the mistakes LLMs make are simple enough to be fixed without destroying the content. I searched for a lightweight python package that was able to reliably fix this problem but couldn't find any. So I wrote one How to use from json_repair import repair_json good_json_string = repair_json(bad_json_string) # If the string was super broken this will return an empty string You can use this library to completely replace `json.loads()`: import json_repair decoded_object = json_repair.loads(json_string) or just import json_repair decoded_object = json_repair.repair_json(json_string, return_objects=True) Read json from a file or file descriptor JSON repair provides also a drop-in replacement for `json.load()`: import json_repair try: file_descriptor = open(fname, 'rb') except OSError: ... with file_descriptor: decoded_object = json_repair.load(file_descriptor) and another method to read from a file: import json_repair try: decoded_object = json_repair.from_file(json_file) except OSError: ... except IOError: ... Keep in mind that the library will not catch any IO-related exception and those will need to be managed by you Performance considerations If you find this library too slow because is using `json.loads()` you can skip that by passing `skip_json_loads=True` to `repair_json`. Like: from json_repair import repair_json good_json_string = repair_json(bad_json_string, skip_json_loads=True) I made a choice of not using any fast json library to avoid having any external dependency, so that anybody can use it regardless of their stack. Some rules of thumb to use: - Setting `return_objects=True` will always be faster because the parser returns an object already and it doesn't have serialize that object to JSON - `skip_json_loads` is faster only if you 100% know that the string is not a valid JSON - If you are having issues with escaping pass the string as **raw** string like: `r"string with escaping\"" Adding to requirements Please pin this library only on the major version! We use TDD and strict semantic versioning, there will be frequent updates and no breaking changes in minor and patch versions. To ensure that you only pin the major version of this library in your `requirements.txt`, specify the package name followed by the major version and a wildcard for minor and patch versions. For example: json_repair==0.* In this example, any version that starts with `0.` will be acceptable, allowing for updates on minor and patch versions. How it works This module will parse the JSON file following the BNF definition:
partialjson
PartialJson is a Python library that allows users to parse partial and incomplete JSON data with ease. With just 3 lines of Python code, users can parse JSON data that may be missing key elements or contain errors. The library provides a simple solution for handling JSON data that may not be well-formed or complete, making it a valuable tool for data processing and manipulation tasks.
floneum
Floneum is a graph editor that makes it easy to develop your own AI workflows. It uses large language models (LLMs) to run AI models locally, without any external dependencies or even a GPU. This makes it easy to use LLMs with your own data, without worrying about privacy. Floneum also has a plugin system that allows you to improve the performance of LLMs and make them work better for your specific use case. Plugins can be used in any language that supports web assembly, and they can control the output of LLMs with a process similar to JSONformer or guidance.
qb
QANTA is a system and dataset for question answering tasks. It provides a script to download datasets, preprocesses questions, and matches them with Wikipedia pages. The system includes various datasets, training, dev, and test data in JSON and SQLite formats. Dependencies include Python 3.6, `click`, and NLTK models. Elastic Search 5.6 is needed for the Guesser component. Configuration is managed through environment variables and YAML files. QANTA supports multiple guesser implementations that can be enabled/disabled. Running QANTA involves using `cli.py` and Luigi pipelines. The system accesses raw Wikipedia dumps for data processing. The QANTA ID numbering scheme categorizes datasets based on events and competitions.
merlin
Merlin is a groundbreaking model capable of generating natural language responses intricately linked with object trajectories of multiple images. It excels in predicting and reasoning about future events based on initial observations, showcasing unprecedented capability in future prediction and reasoning. Merlin achieves state-of-the-art performance on the Future Reasoning Benchmark and multiple existing multimodal language models benchmarks, demonstrating powerful multi-modal general ability and foresight minds.
json-translator
The json-translator repository provides a free tool to translate JSON/YAML files or JSON objects into different languages using various translation modules. It supports CLI usage and package support, allowing users to translate words, sentences, JSON objects, and JSON files. The tool also offers multi-language translation, ignoring specific words, and safe translation practices. Users can contribute to the project by updating CLI, translation functions, JSON operations, and more. The roadmap includes features like Libre Translate option, Argos Translate option, Bing Translate option, and support for additional translation modules.
model-catalog
model-catalog is a repository containing standardized JSON descriptors for Large Language Model (LLM) model files. Each model is described in a JSON file with details about the model, authors, additional resources, available model files, and providers. The format captures factors like model size, architecture, file format, and quantization format. A Github action merges individual JSON files from the `models/` directory into a `catalog.json` file, which is validated using a JSON schema. Contributors can help by adding new model JSON files following the contribution process.
sparrow
Sparrow is an innovative open-source solution for efficient data extraction and processing from various documents and images. It seamlessly handles forms, invoices, receipts, and other unstructured data sources. Sparrow stands out with its modular architecture, offering independent services and pipelines all optimized for robust performance. One of the critical functionalities of Sparrow - pluggable architecture. You can easily integrate and run data extraction pipelines using tools and frameworks like LlamaIndex, Haystack, or Unstructured. Sparrow enables local LLM data extraction pipelines through Ollama or Apple MLX. With Sparrow solution you get API, which helps to process and transform your data into structured output, ready to be integrated with custom workflows. Sparrow Agents - with Sparrow you can build independent LLM agents, and use API to invoke them from your system. **List of available agents:** * **llamaindex** - RAG pipeline with LlamaIndex for PDF processing * **vllamaindex** - RAG pipeline with LLamaIndex multimodal for image processing * **vprocessor** - RAG pipeline with OCR and LlamaIndex for image processing * **haystack** - RAG pipeline with Haystack for PDF processing * **fcall** - Function call pipeline * **unstructured-light** - RAG pipeline with Unstructured and LangChain, supports PDF and image processing * **unstructured** - RAG pipeline with Weaviate vector DB query, Unstructured and LangChain, supports PDF and image processing * **instructor** - RAG pipeline with Unstructured and Instructor libraries, supports PDF and image processing. Works great for JSON response generation
ollama-grid-search
A Rust based tool to evaluate LLM models, prompts and model params. It automates the process of selecting the best model parameters, given an LLM model and a prompt, iterating over the possible combinations and letting the user visually inspect the results. The tool assumes the user has Ollama installed and serving endpoints, either in `localhost` or in a remote server. Key features include: * Automatically fetches models from local or remote Ollama servers * Iterates over different models and params to generate inferences * A/B test prompts on different models simultaneously * Allows multiple iterations for each combination of parameters * Makes synchronous inference calls to avoid spamming servers * Optionally outputs inference parameters and response metadata (inference time, tokens and tokens/s) * Refetching of individual inference calls * Model selection can be filtered by name * List experiments which can be downloaded in JSON format * Configurable inference timeout * Custom default parameters and system prompts can be defined in settings
t3rn-airdrop-bot
A bot designed to automate transactions and bridge assets on the t3rn network, making the process seamless and efficient. It supports multiple wallets through a JSON file containing private keys, with robust error handling and retry mechanisms. The tool is user-friendly, easy to set up, and supports bridging from Optimism Sepolia and Arbitrum Sepolia.
MyScaleDB
MyScaleDB is a SQL vector database optimized for AI applications, enabling developers to manage and process massive volumes of data efficiently. It offers fast and powerful vector search, filtered search, and SQL-vector join queries, making it fully SQL-compatible. MyScaleDB provides unmatched performance and scalability by leveraging cutting-edge OLAP database architecture and advanced vector algorithms. It is production-ready for AI applications, supporting structured data, text, vector, JSON, geospatial, and time-series data. MyScale Cloud offers fully-managed MyScaleDB with premium features on billion-scale data, making it cost-effective and simpler to use compared to specialized vector databases. Built on top of ClickHouse, MyScaleDB combines structured and vector search efficiently, ensuring high accuracy and performance in filtered search operations.
transcribe-anything
Transcribe-anything is a front-end app that utilizes Whisper AI for transcription tasks. It offers an easy installation process via pip and supports GPU acceleration for faster processing. The tool can transcribe local files or URLs from platforms like YouTube into subtitle files and raw text. It is known for its state-of-the-art translation service, ensuring privacy by keeping data local. Notably, it can generate a 'speaker.json' file when using the 'insane' backend, allowing speaker-assigned text de-chunkification. The tool also provides options for language translation and embedding subtitles into videos.
funcchain
Funcchain is a Python library that allows you to easily write cognitive systems by leveraging Pydantic models as output schemas and LangChain in the backend. It provides a seamless integration of LLMs into your apps, utilizing OpenAI Functions or LlamaCpp grammars (json-schema-mode) for efficient structured output. Funcchain compiles the Funcchain syntax into LangChain runnables, enabling you to invoke, stream, or batch process your pipelines effortlessly.
deepdoctection
**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.
strictjson
Strict JSON is a framework designed to handle JSON outputs with complex structures, fixing issues that standard json.loads() cannot resolve. It provides functionalities for parsing LLM outputs into dictionaries, supporting various data types, type forcing, and error correction. The tool allows easy integration with OpenAI JSON Mode and offers community support through tutorials and discussions. Users can download the package via pip, set up API keys, and import functions for usage. The tool works by extracting JSON values using regex, matching output values to literals, and ensuring all JSON fields are output by LLM with optional type checking. It also supports LLM-based checks for type enforcement and error correction loops.
go-cyber
Cyber is a superintelligence protocol that aims to create a decentralized and censorship-resistant internet. It uses a novel consensus mechanism called CometBFT and a knowledge graph to store and process information. Cyber is designed to be scalable, secure, and efficient, and it has the potential to revolutionize the way we interact with the internet.
rpaframework
RPA Framework is an open-source collection of libraries and tools for Robotic Process Automation (RPA), designed to be used with Robot Framework and Python. It offers well-documented core libraries for Software Robot Developers, optimized for Robocorp Control Room and Developer Tools, and accepts external contributions. The project includes various libraries for tasks like archiving, browser automation, date/time manipulations, cloud services integration, encryption operations, database interactions, desktop automation, document processing, email operations, Excel manipulation, file system operations, FTP interactions, web API interactions, image manipulation, AI services, and more. The development of the repository is Python-based and requires Python version 3.8+, with tooling based on poetry and invoke for compiling, building, and running the package. The project is licensed under the Apache License 2.0.
text-extract-api
The text-extract-api is a powerful tool that allows users to convert images, PDFs, or Office documents to Markdown text or JSON structured documents with high accuracy. It is built using FastAPI and utilizes Celery for asynchronous task processing, with Redis for caching OCR results. The tool provides features such as PDF/Office to Markdown and JSON conversion, improving OCR results with LLama, removing Personally Identifiable Information from documents, distributed queue processing, caching using Redis, switchable storage strategies, and a CLI tool for task management. Users can run the tool locally or on cloud services, with support for GPU processing. The tool also offers an online demo for testing purposes.
pgai
pgai simplifies the process of building search and Retrieval Augmented Generation (RAG) AI applications with PostgreSQL. It brings embedding and generation AI models closer to the database, allowing users to create embeddings, retrieve LLM chat completions, reason over data for classification, summarization, and data enrichment directly from within PostgreSQL in a SQL query. The tool requires an OpenAI API key and a PostgreSQL client to enable AI functionality in the database. Users can install pgai from source, run it in a pre-built Docker container, or enable it in a Timescale Cloud service. The tool provides functions to handle API keys using psql or Python, and offers various AI functionalities like tokenizing, detokenizing, embedding, chat completion, and content moderation.
island-ai
island-ai is a TypeScript toolkit tailored for developers engaging with structured outputs from Large Language Models. It offers streamlined processes for handling, parsing, streaming, and leveraging AI-generated data across various applications. The toolkit includes packages like zod-stream for interfacing with LLM streams, stream-hooks for integrating streaming JSON data into React applications, and schema-stream for JSON streaming parsing based on Zod schemas. Additionally, related packages like @instructor-ai/instructor-js focus on data validation and retry mechanisms, enhancing the reliability of data processing workflows.
20 - OpenAI Gpts
Process Map Optimizer
Upload your process map and I will analyse and suggest improvements
Process Engineering Advisor
Optimizes production processes for improved efficiency and quality.
Customer Service Process Improvement Advisor
Optimizes business operations through process enhancements.
R&D Process Scale-up Advisor
Optimizes production processes for efficient large-scale operations.
Process Optimization Advisor
Improves operational efficiency by optimizing processes and reducing waste.
Manufacturing Process Development Advisor
Optimizes manufacturing processes for efficiency and quality.
Trademarks GPT
Trademark Process Assistant, Not an Attorney & Definitely Not Legal Advice (independently verify info received). Gain insights on U.S. trademark process & concepts, USPTO resources, application steps & more - all while being reminded of the importance of consulting legal pros 4 specific guidance.
Prioritization Matrix Pro
Structured process for prioritizing marketing tasks based on strategic alignment. Outputs in Eisenhower, RACI and other methodologies.
👑 Data Privacy for Insurance Companies 👑
Insurance providers collect and process personal health, financial, and property information, making it crucial to implement comprehensive data protection strategies.
ScriptCraft
To streamline the process of creating scripts for Brut-style videos by providing structured guidance in researching, strategizing, and writing, ensuring the final script is rich in content and visually captivating.
Notes Master
With this bot process of making notes will be easier. Send your text and wait for the result
Cali - ISO 9001 Professor
I will give you all the information about the Audit and Certification process of ISO 9001 Management Systems, either in the form of a specialization course or consultations.