Tara AI

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Tara AI is an AI-powered platform designed to enhance software engineering processes by providing actionable insights and metrics for better decision-making.

How Tara AI can help you:

Unify and enrich engineering activity without altering your teams’ workflows.
Provide real-time insights and alerts on project delivery and efficiency.
Aggregate performance data to uncover meaningful insights at both team and project levels.
Offer improved visibility into hurdles in engineering operations with real-time notifications.
Enable prioritization of initiatives that deliver actual customer value by assessing impact at the feature and project level.

Why choose Tara AI: Key features

Integration with issue tracking and Git source control for comprehensive insights.
Real-time visibility across the development cycle with active syncing to current tools.
Detailed analytics on engineering efficiency and customer delivery.
Tools for effectively communicating project status and identifying areas for improvement.

Who should choose Tara AI:

Software engineering teams looking to measure and optimize their workflows.
Engineering leaders needing a comprehensive overview of delivery metrics.
Organizations aiming to align engineering efforts with customer value.

About Tara AI

Website

https://tara.ai

Release Date

March 2024

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Atlassian's Rovo AI Assistant Now Generally Available, Bringing AI-Powered Productivity to Teams

Atlassian has announced the general availability of Rovo, its AI-powered assistant, along with new AI features across its product suite and updates to Jira. Rovo aims to enhance team productivity by providing intelligent search, chat, and automation capabilities.

5 Sources

Wed, 9 Oct, 4:02 PM UTC

Top 6 AI tools for the modern employee

AI-powered tools have the potential to make mundane, laborious work manageable, leaving you the time to tackle the tasks that matter most. AI has received its fair share of criticism lately, with topics such as biased hiring, employment insecurity and unsafe data storage dominating the conversation. Whereas all of the above is true and the regulation and ethical scrutinising of AI is vital to the advancement of present and future technologies, AI, when used responsibly can be a gamechanger in the workplace. From data-based decision making and collaboration, to increased DEI engagement and improved workflow, AI tools, when treated like an asset rather than an additional employee, can boost productivity and give time back to the workforce. So, what AI tools should the modern employee be using in 2024? ChatGPT ChatGPT, when used to its full potential, is an AI-powered platform that can offer significant assistance in the workplace. It does, however, come with a caveat of sorts. Due to issues of ownership and authenticity, many employers, institutions and organisations will rightly insist upon an iron-clad ChatGPT policy. If your organisation allows the use of ChatGPT to aid you in your work, there are a number of ways in which it can be incredibly useful. For example, if you are dealing with a complex subject matter, you can paraphrase it and ask the app to explain what it means using basic language and terminology. It offers a range of time-saving features, such as the ability to compile and summarise research, translate foreign languages and generate workflow templates. As long as you view ChatGPT as an assist, rather than a replacement for your own work, you can't go wrong. Just make sure your use of the technology is in line with company policy. Grammarly Pobody's nerfect and we all learn from our mistakes, but they are still best avoided where possible. AI-based writing assistant Grammarly, which can be installed as a browser extension or plugin, helps ensure that your writing is not only correct in terms of grammar and punctuation, but that the tone is right and the piece readable. It can be installed on a range of devices and aims to improve your writing overall, not just from a technical point of view. It is also an invaluable tool for anyone who may have additional needs, for example people with dyslexia, or those with visual or auditory conditions, as it has an in-built text-to-speech function. Consensus If you are working in academia then you are likely no stranger to long days and nights of research, information storing and note-taking. It can be an exhausting, time-consuming activity that may not always bear fruit. Consensus is an AI-powered academic search engine that gives users access to more than 200m peer-reviewed, science-based research papers. If you are getting bogged down in the information overload, Consensus can help redirect your focus and get you back on track. Github Copilot For the programmers among us, Github Copilot is essentially an app that operates as a coding buddy. Writing and reviewing code takes a great deal of energy, time and patience, as one misplaced dot has the potential to undermine hours of work. Join us to create the technology of tomorrow Join us to start Caring. Connecting. Growing together Building relationships, creating value Unlocking the potential of biology for patients As you 'partner' with Github Copilot, it can make suggestions relating to code, offer help via a chat feature, track changes and create and manage collections of documentation, to be used contextually as you engage with the chat functions. For those who code frequently, Github Copilot can increase writing speed, accelerate work and leave more time for problem-solving. Otter.ai If a significant portion of your work involves phone, video or in-person conversations that have to be recorded for later use, then Otter.ai, or similar AI-powered transcription apps are an absolute must. The platform, which can easily be integrated with a wide variety of existing workplace programmes, can record conversations and meetings, transcribe content and be shared across multiple teams. Search features enable you to seek out specific aspects of the conversation and the app will also make note of the different speakers throughout. You can even access a brief summary of the conversation, to get the gist of a call, without having to listen back or read the full document. Canva Online design and visual communication platform Canva is ideal for anyone whose role depends on creating captivating visual content. Its easy to navigate interface makes it a perfect choice for people who are starting out, as well as those with more experience. Users can customise graphics, images and text to fit a specific design choice, or make use of pre-existing templates. The usability of Canva across a wide variety of social media platforms also makes it a great choice for employees looking to extend their reach and engage with a broader audience. Canva is a useful AI tool as it can save an employee a significant amount of time, while still producing a professional looking image. It also enables users to view metrics of success to determine the who and hows of public engagement. When used correctly, that is to say as a helping hand, rather than an easy-fix, AI-powered tools can revolutionise the workplace, making operations run that little bit smoother. So, why not experiment with a few and see how they improve your day-to-day workplace activities? Don't miss out on the knowledge you need to succeed. Sign up for the Daily Brief, Silicon Republic's digest of need-to-know sci-tech news.

Silicon Republic

Fri, 11 Oct, 12:01 PM UTC

Impacts of AI revealed in TestRail report

Artificial Intelligence Impacts of AI revealed in TestRail report Tuesday, October 15, 2024 Richard Harris TestRail's latest report, "Exploring the Impact of AI in QA," analyzes insights from over 1,000 QA professionals to provide a realistic view of AI's role in quality assurance. It highlights AI-driven efficiency, adoption barriers, and future optimism for AI's transformative potential. TestRail announced its latest report, "Exploring the Impact of AI in QA." Based on the QA industry's first AI-focused research survey, this comprehensive report draws on insights from over 1,000 QA professionals and aims to cut through the hype surrounding artificial intelligence, offering a clear and accurate picture of how QA teams are adopting, planning for, and responding to AI technology. The research explores AI's applications in areas such as regression testing, test automation, and performance testing, revealing how AI is helping teams increase efficiency, improve test coverage, and enhance overall quality. Key impacts of AI, according to TestRail's latest report AI Adoption and Success: A significant 65% of survey respondents reported using AI in their QA processes, with AI being applied uniformly across various testing types. However, certain use cases show more potential than others. AI-Driven Productivity Gains: Over 50% of respondents reported increased productivity and improved test coverage, underscoring AI's potential to enhance testing efficiency. AI's Versatility: AI is proving effective across various testing types, including regression, smoke, and performance testing. It is being used to generate test cases, execute tests, and analyze results, allowing human testers to focus on strategic tasks. Barriers to Adoption: Despite high adoption rates, challenges like AI's complexity, concerns about data privacy and security, and uncertainty about its benefits continue to hinder broader implementation. Actionable Tips: The report also offers practical tips, strategies, and prompt ideas from industry experts and survey respondents, empowering QA managers to start leveraging AI in their own processes today. Most importantly, the report also details the QA community's overwhelmingly optimistic outlook on the future of AI, despite adoption challenges -- a perspective that TestRail fully supports. Exploring the Impact of AI in QA "Although it's still early to gauge AI's full impact on QA, we think the future looks bright. Like test automation before it, we're optimistic that AI will not only speed up release cycles and improve software quality but also empower testers to spend more time on tasks that require human insight and intuition. As long as software is made for people, the human element in testing will remain essential," said Judy Bossi, VP of Product at Idera. AI can assist with various stages of the QA process, making life easier for QA professionals. From crafting test cases to analyzing results, QA teams are seeing success leveraging AI for a wide assortment of quality tasks. Here's a look at a few ways it's being used: Creating and managing test cases: AI helps design test cases more quickly and efficiently and even prioritizes them based on risk. Automating tests: With AI, writing and refining test scripts is faster and easier. It also helps to debug and keep test cases up to date. Handling test data: AI generates realistic synthetic data, masks sensitive information, and speeds up data preparation. Analyzing results: AI enhances how we analyze performance, predict defects, and review test outcomes, providing deeper insights into application health. Debugging code: AI offers valuable assistance in analyzing code, suggesting fixes, and spotting anomalies, which speeds up the debugging process. These examples show just how integrated AI is becoming in the QA process, helping to make testing more efficient and effective. The survey found that 54% of respondents experienced a modest boost in productivity and coverage, and 43% saw a significant improvement. These results confirm that AI is quickly proving its usefulness l in QA, delivering real benefits and setting the stage for even greater advancements as the technology evolves. The survey results revealed that AI in QA is still finding its footing. Early indications are positive, but QA professionals are still figuring out the best ways to integrate AI into their testing processes. Even though AI is relatively new and often discussed with a focus on its risks and uncertainties, those who are already using it are genuinely optimistic. This optimism is a clear sign that, despite the hurdles, AI is making a real impact and people are excited about what's to come. Become a subscriber of App Developer Magazine for just $5.99 a month and take advantage of all these perks. MEMBERS GET ACCESS TO- Exclusive content from leaders in the industry - Q&A articles from industry leaders - Tips and tricks from the most successful developers weekly - Monthly issues, including all 90+ back-issues since 2012 - Event discounts and early-bird signups - Gain insight from top achievers in the app store - Learn what tools to use, what SDK's to use, and more Subscribe here Impacts of AI revealed in TestRail report, AI adoption, QA processes, Test automation, Regression testing, Productivity gains, Data privacy, Testrail, AI Technology share

App Developer Magazine

Tue, 15 Oct, 8:28 PM UTC

AI Code Review Tools: Should You Use Them? - DZone

Artificial intelligence (AI) is entering various industries, offering numerous advantages to fields like software coding and development. Today, many development teams have adopted AI code review tools and noticed how much faster they catch errors and improve code quality. Yet, with any new technology, there are questions about its limitations, especially with security and accuracy. AI coding tools are software solutions that leverage artificial intelligence to analyze and improve code. Traditionally, code reviews require peers or senior developers to conduct this process manually, but it can be time-consuming and prone to human oversight. AI code review tools automate much of this process by using machine learning and natural language processing to detect anomalies, bugs, and security vulnerabilities in the code. These tools work by scanning code quickly to find common errors, security gaps, and inefficient logic. Then, it will provide suggestions for improvements. Tools like GitHub Copilot, CodeRabbit, and Codium AI can analyze lines of code and flag problematic areas. They even offer fixes in real time or during the review process. The AI behind these tools requires data scientists to train them on massive datasets of code. This helps them learn from previous reviews and continuously improve suggestions over time. AI code review tools had a market size of $4.86 billion in 2023, and researchers project it to grow at a compound annual growth rate of 27.1% from 2024 to 2030. This expansion suggests that more industries will use AI to streamline development and workflows and enhance code quality. When developers use AI code review tools, many find they offer several of the following advantages: Humans reviewing code vary in attention to detail and approach based on experience. Plus, the task itself takes time, which can cause burnout and make it more difficult to find flaws. Yet, with AI tools, developers can streamline the process as it maintains a uniform standard of analysis across all reviews. They apply the same criteria to every piece of code, ensuring that vulnerabilities or errors do not exist. As such, they can reduce overlooked instances due to human error or fatigue. This consistency helps development teams maintain a higher standard of code quality, especially in large projects that require several team members. The rate at which these tools operate is another major benefit. Since manual code reviews are time-consuming, AI solutions can analyze large amounts of code in a short period. With their instantaneous speed, they can identify issues in a fraction of the time it would take a human. This quick analysis allows developers to receive real-time feedback, enabling them to optimize their code as they write it. Developers are always on a time crunch, from dealing with unrealistic deadlines to fixing bugs and meeting new requirements. With limited availability to review code, developers can turn to AI tools whenever needed. As a result of their 24/7 availability, they can complete their reviews right on time. This means professionals can maintain their momentum on projects and address issues as soon as they arise. AI code review tools may have many advantages, but it is important for those working with code to consider their downfalls. A pressing concern with AI code reviewers is they come with security risks. While these tools can identify vulnerabilities and improve code quality, they are not foolproof. In fact, Snyk's experience with AI code review tools revealed that these systems suggested insecure code. However, its survey found that 75.8% of respondents believed AI-generated code was more secure than human-written code. Many developers feel confident about using these tools, but this may come from an increased need to understand how AI operates and its security concerns. While AI can be an asset, the same survey also revealed that 56% of developers admitted that these software solutions sometimes or often introduce coding issues like security vulnerabilities. Therefore, it is important to educate technology teams about the limitations of secure development. Meanwhile, proper oversight is key, as it still needs human reviewers to guarantee reduced vulnerabilities. AI tools have yet to reach perfection, as they can sometimes flag non-issues as potential problems. Or, they may fail to identify genuine code vulnerabilities. False positives can frustrate developers, as they force them to spend unnecessary time addressing warnings that are not a real threat to the code. Over time, this can lead to "alert fatigue," causing software professionals to dismiss valid warnings. Conversely, false negatives are even more concerning because they allow actual code flaws to slip through the cracks. This issue may lead to inefficient or insecure code once it is live. AI often lacks the ability to understand the broader context or intent behind the code. This can lead to inappropriate suggestions or missed issues that a human reviewer would likely catch. For example, AI tools may flag certain parts of the code as inefficient or redundant without understanding why a developer made those choices to meet a certain requirement. Additionally, when reviewing specialized code, the tool may overlook dependencies that are critical to the application's proper functioning. This lack of contextual awareness can lead to issues for developers when they must ignore irrelevant feedback. The benefits are clear with AI review tools: However, it is crucial to use them with their limitations in mind. Given their drawbacks, AI tools are best for pre-reviews rather than full code reviews. In other words, they can be highly effective in catching surface-level issues early on, but a project should still require thorough human review. When using AI for code review, developers can take advantage of these tools' full benefits. However, they do have limitations. That is why creators should use them thoughtfully. Leveraging their strengths while staying mindful of their weaknesses will allow for a more efficient and secure development process.

dzone.com

Thu, 17 Oct, 8:02 PM UTC

The Best Generative AI Workplace Productivity Tools

By now everyone's probably seen generative AI tools like ChatGPT and Midjourney that can create text, drawings and even computer code that look like they've been made by humans. They're highly impressive, but are you just using them for fun, or have you worked out how to get them to do something that's truly useful? Well, one of the areas where they have the most potential is automating day-to-day workplace tasks. In the last two years, many new apps, tools and services have appeared that can help us become quicker and more productive at work. So here's my roundup of what I believe are some of the most impressive, useful or innovative generative AI productivity tools available today. They can help anyone to do their job quicker or more efficiently, saving valuable time that can be spent on more rewarding and creative tasks. These are in no particular order, but let's start with five that I think are particularly interesting or noteworthy: Zapier Zapier is an integration tool, which means it helps other tools and applications talk to each other and work collaboratively. For example, it can be used to automatically log information from sources like call logs, emails, or chat transcripts and used to create to-do cards in project management tools like Trello, calendar events, or update records in CRM software like SalesForce or Hubspot. This can save users huge amounts of time that would be spent copying and updating records across different platforms. It also reduces the chances of human error. Zapier has now integrated generative AI chatbots that make this process as simple as telling them what you want it to do. It will automatically find the right connectors and triggers, and pull out insights from real-time business data, This makes it simple for anyone to build AI workflows involving multiple applications and data sources. Otter.ai In recent years, Otter has emerged as one of the leading AI-powered meeting assistants. It can automatically create transcripts of conversations that can be organized and searched, as well as extract insights and action items. It integrates with popular messaging and meeting apps like Zoom and Teams and can generate email summaries and send them out to relevant people while keeping track of any follow-ups that are needed. One of the things that set it apart is its high level of user-friendliness, meaning that even colleagues who are nervous about trying out new tools should be able to start making use of its AI features very quickly. Trello Millions of people use project management tools to keep track of ongoing work or measure progress toward goals, and Trello is one of the most popular. Like many industry standard tools, it's recently been powered up with the inclusion of generative AI features, in this case provided by the Atlassian Intelligence engine. This streamlines the process of creating new cards by generating content and automated summaries, as well as even suggesting improvements for grammar or clarity when communicating your ideas. Atlassian Intelligence is only available to premium and enterprise Trello users at the moment but may be integrated into the free version in the future. Zoom With AI Companion Zoom established itself as an everyday tool during the COVID-19 pandemic, helping many companies carry on with business (almost) as usual. Many more of us discovered it was also a great way to keep in touch with family and friendship groups. More recently, it, too, has received a generative AI makeover thanks to the addition of Workplace Companion. With this, users with a paid-for subscription can create automated summaries of calls and virtual meetings, along with follow-ups, assignments and action points. This eliminates the need to take notes and other manual administrative actions during meetings and lets attendees focus on the discussion at hand. BeeDone BeeDone takes a different approach to many of the productivity apps here by gamifying the process of task management. It does this by breaking complex tasks down into simple steps and then awarding points for completing them. It's a fun idea that adds a new spin on the numerous "smart" to-do lists, task managers and time trackers that are available. BeeDone learns users' habits and fine-tunes its ability to optimize processes and even includes "productivity tournaments" where users can compete against each other to see who can become the most efficient! There are many more tools that let anyone put generative AI to work to streamline routine workday tasks; here are some more of the best that I've come across: Asana Automate project management and workflow tasks and manage calendars. Avoma This AI meeting assistant transcribes meetings but also provides coaching insights to help users improve their communication and engagement skills. Beautiful Transform ideas into fully realized slides and presentations with automated design features. Clara Clara is an AI assistant that aims to act as a virtual employee, scheduling meetings, communicating between attendees and adding details to your calendar once they've been established. ClickUp Generative AI-driven workplace productivity suite with project management, time tracking, whiteboarding, agendas and other features. Clockwise Time-management tool that can automate scheduling to help teams make more efficient use of their time. Decktopus Generate slide decks and presentations from natural language prompts. Duet Another Google service, this one, is built into Workspace to provide a collaborative assistant for productivity tasks. EmailTree Email management and customer service platform with features like automatic reply suggestions, multilingual support, team management, CRM, sentiment analysis, and automation. Fireflies Transcribe, summarize and search voice conversations. Gamma Automates the creation of presentations and various types of documents with the help of generative AI. Mailbutler Integrates with common email applications to provide tools that automate composing, summarizing and responding to emails. AI-powered workspace that manages tasks as well as offers functions like document summarization and content creation. Reclaim AI-powered calendar management and time tracking. Sanebox AI-powered email management that analyzes incoming mail, sorts it into relevant folders and generates reminders and auto-responses. Tome Leverage AI storytelling to create compelling decks and presentations using GPT-4o technology.

Forbes

Tue, 16 Jul, 6:00 AM UTC

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