Inventive AI’s Post

Curious about integrating generative AI into your organisations bid process? In this week's article, we discuss increasing productivity, efficiency, and team satisfaction with AutogenAI. Read the full article below. #generativeai #artificialintelligence #ai #bidwriting #proposalwriting #augmentedintelligence

In today’s fast-paced business environment, self-service portals have become essential tools that empower users to manage their needs efficiently. However, the true value of a self-service portal lies in its ability to facilitate the seamless flow of information within an organisation. Building from the inside out means starting with the structured information and data that already exists within your organisation. But what exactly do we mean and how does that impact you and your organisation? earn more about what we mean here #GrowWithTheFlow #InformationUnbound #ConnectingSystems #documentmanagement #BusinessProcessAutomation #BPA #Knowledgeworkautomation #AI #SelfServicePortal #SelfServicePortal

An interesting and useful article on the value of self service portals. We’ll be covering this topic in one of our upcoming webinars that you can register at www.convergent.ie

Curious about integrating generative AI into your organisations bid process? Then check this out! In this week's article, we discuss increasing productivity, efficiency, and team satisfaction with AutogenAI Read the full article below. ⬇ #generativeai #artificialintelligence #ai #bidwriting #proposalwriting #augmentedintelligence #autogenai #apac

Curious about integrating generative AI into your organisations bid process? In this week's article, we discuss increasing productivity, efficiency, and team satisfaction with AutogenAI. Read the full article below. #generativeai #artificialintelligence #ai #bidwriting #proposalwriting #augmentedintelligence

AutogenAI is a generative AI software that helps bid teams streamline their processes and increase their chances of winning contracts 🤝 It expedites bid-no bid decisions, aids in strategy formulation, and produces high-quality draft responses in a fraction of the time 🤩 AutogenAI provides well-researched content and improves team productivity ✅ Generative AI is revolutionising bid teams' operations, and AutogenAI is leading the way in this revolution ✨ Embracing generative AI is becoming a necessity for staying ahead in the bidding game. 🚀 ------------------------------------------ Written in collaboration with AutogenAI's General Language Engine 1 (Genny1)

An open compatison between commercial off-the-shelf (COTS) AI products and open-source AI products / tools depends on various factors, including the specific needs of your project, available resources, and desired level of customization and support. Here's a comparison: 1. **Cost**: - COTS AI products often involve licensing fees or subscription costs, which can be significant depending on the scale of usage. - Open-source AI tools are typically free to use, but may require investment in training, customization, and maintenance. 2. **Features and Functionality**: - COTS AI products may offer comprehensive features and advanced functionalities out of the box, tailored to specific use cases. - Open-source AI tools provide flexibility for customization and integration with other systems, but may require more effort to implement advanced features. 3. **Customization and Control**: - COTS AI products may have limitations in terms of customization, as users rely on the vendor to provide updates and new features. - Open-source AI tools offer greater control and flexibility, allowing users to modify the code to suit their specific requirements. 4. **Support and Maintenance**: - COTS AI products often come with dedicated support services, including troubleshooting, updates, and maintenance. - Open-source AI tools rely on community support, forums, and documentation, although commercial support options are available for some popular projects. 5. **Security and Compliance**: - COTS AI products may have robust security features and compliance measures built-in, addressing regulatory requirements. - Open-source AI tools require careful management of security risks and compliance considerations, as users have more control over the implementation. 6. **Ease of Implementation**: - COTS AI products are designed for ease of use and may have user-friendly interfaces, making them accessible to a broader audience. - Open-source AI tools may require more technical expertise for setup, configuration, and integration into existing systems. In summary:: COTS AI products offer convenience, comprehensive features, and support services, but come with associated costs and potential limitations in customization. Open-source AI tools provide flexibility, control, and cost-effectiveness, but require more effort in terms of implementation and ongoing maintenance. The choice is based on your budget & how big or small your pocket is ? 🤷🏻♂️🤷🏻♂️

The 5 key questions you should ask your Intelligent Document Processing (IDP) vendor (via Rich Medina) 𝟏. 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧: Can the vendor effectively develop or integrate advanced AI/ML capabilities? They should be advancing beyond basic extraction methods like rule-, template-, and zone-based approaches, as well as regular expressions and keyword searches. Ideally, they should employ more sophisticated techniques such as support vector machines, while also having a technical roadmap that includes large language models (LLMs) and transformer models. Most vendors will achieve this through technical integrations and partnerships. Avoid settling for vague answers like 'secret special sauce' or implicit vendor know-how. 𝐂𝐨𝐦𝐩𝐥𝐞𝐭𝐞𝐧𝐞𝐬𝐬: Do you offer all the necessary IDP capabilities? It's not just about the engine – what about the entire vehicle? The 'vehicle' in IDP includes the essential framework that makes the engines usable, including document capture, workflow, orchestration, human-in-the-loop (HIL) integration, administration, and reporting. Currently, no single vendor excels in both IDP engines and frameworks. 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Is your solution market-ready? Assess whether the vendor can successfully productize, market, sell, deliver, and support their IDP capabilities. Beware of entrusting your IDP needs to, for example, startups operating from a garage, regardless of how impressive their transformer-based extraction methods may seem. It's safer to share IDP costs and risks with peer organizations than to gamble on a unique, unproven technology in this volatile field. 𝐂𝐨𝐧𝐬𝐮𝐦𝐩𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧: Can your organization effectively implement and use the IDP solution? Evaluate whether your team can successfully implement, launch, and maintain these capabilities while achieving a satisfactory ROI. Transitioning from a dated capture operation to modern IDP can be challenging due to the differences in tasks and new AI-related roles. One aspect to monitor closely is the framework or 'vehicle' of the solution. Many suppliers focus on the HIL and workflow without understanding that production capture requires a 'factory' approach, emphasizing speed and ergonomic efficiency with hotkeys instead of a mouse, and finding ways to minimize eye and hand fatigue. 𝐏𝐫𝐞𝐜𝐢𝐬𝐢𝐨𝐧: How do you address accuracy challenges in advanced IDP? Can they minimize errors like hallucinations or false positives, common in technologies like LLMs. Reliable IDP vendors actively work on enhancing precision, for example, through advanced quality control techniques. At a minimum, they should be cognizant of these issues and address them in their technical roadmap. No provider has completely resolved these issues yet. However, the leading suppliers are developing realistic roadmaps and forming partnerships to tackle these challenges in the coming years. For further inquiries about IDP strategy and solutions, contact Doculabs.

Award-winning writer Brian Sommer, MBA, starts his recent diginomica article with an important warning. "Don't buy your next ERP, CRM, HRMS, etc. solution quite so fast. You might want to seriously investigate what each vendor is doing (or not) vis-à-vis its new AI-fueled applications/solutions. If you're used to using some old boilerplate as the guts of a software RFP, here are some important additions to that workhorse documentation." His article dives deep into critical questions you should ask, categorized into key areas: 𝗜𝗻𝗱𝗲𝗺𝗻𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 & 𝗥𝗶𝘀𝗸: - Who's responsible for outputs, especially if third-party models or data are involved? - How can AI tools be recalibrated or adjusted if needed? - What safeguards are in place to monitor and control outputs? 𝗘𝗦𝗚 𝗜𝗺𝗽𝗮𝗰𝘁: - What is the environmental and social impact of the cloud data centers where AI tools operate? - Does the vendor use low-carbon energy sources or offset carbon emissions? - How are water and other resources used sustainably? 𝗔𝗜 & 𝗘𝘁𝗵𝗶𝗰𝘀: - Does the vendor have a process for assessing the ethical implications of their AI tools? - How does the vendor ensure their tools avoid biased or discriminatory outputs? - What data is used to train the AI, and how are concerns about privacy and ownership addressed? 𝗣𝗶𝗹𝗼𝘁 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝘀 & 𝗧𝗲𝘀𝘁𝗶𝗻𝗴: - Can you offer limited-use trials or pilot programs to thoroughly test the tool before committing? - What are the refund policies if the tool doesn't meet expectations? 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 & 𝗖𝗼𝗻𝘁𝗿𝗼𝗹: - Does the vendor offer robust monitoring tools to identify and address potential issues with AI outputs? - What training and support are available to ensure responsible use of the tools? 𝗕𝗲𝘆𝗼𝗻𝗱 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆: - What staffing and training implications does adopting new AI tools entail? - Can the vendor provide estimates and resources to address these needs? 𝗥𝗲𝗺𝗲𝗺𝗯𝗲𝗿: Choosing the right software partner in this ever-changing landscape is crucial. By asking 𝘁𝗼𝘂𝗴𝗵 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀, 𝗱𝗲𝗺𝗮𝗻𝗱𝗶𝗻𝗴 𝘁𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝗰𝘆, 𝗮𝗻𝗱 𝗮𝗰𝘁𝗶𝘃𝗲𝗹𝘆 𝘀𝗲𝗲𝗸𝗶𝗻𝗴 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 𝘁𝗵𝗮𝘁 𝗮𝗱𝗱𝗿𝗲𝘀𝘀 𝘁𝗵𝗲𝘀𝗲 𝗰𝗼𝗻𝘀𝗶𝗱𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀, you can harness the power of AI responsibly and ethically to drive your business forward. Set the right expectations and be honest about how much AI will improve your business. Here is a link to Brian's article for more details:

Here's how I use AI to quickly generate client proposals following a sales call in just 15 minutes. This problem had cost me many hours of frustration, until I came up with a great prompt. Here are my steps: 1. Transcribe the call using AI 2. Feed call transcription to my custom GPT 3. Edit the draft and send the proposal One of the biggest bottlenecks I face is transitioning from a call with a prospect to sending a proposal. The longer I wait, the harder it gets. That’s why I like to prepare as much as possible before the call with templates for each case study, etc. Right after the call, I take the transcript generated by my trusty AI (Link in comments) and feed it to a GPT I created. This GPT writes the proposal for me, considering everything discussed and my context (services, audience, etc.). I then refine the output to finalize my proposal, ensuring I don’t miss anything important. Here is my prompt. Copy and make sure to update the [bold parts]. Role: Expert Business Consultant Instructions: Receive and review a call transcript with a lead. Analyze the transcript to extract the following information: 1) The lead’s context/background of their business: Describe their business, the problems they’re facing, previous attempts to solve it, associated costs, losses incurred, the timeframe for solving it, and the implications of not resolving the issue. 2) Scope of work: Detail the specific tasks and activities that need to be done to help them with their problem. Include information such as the frequency and duration of meetings, the specific areas to be addressed, and any other tangible actions required. 3) Proposal elements: Break down the proposal into clear and distinct components, such as coaching calls, review and analysis of the business, initial suggestions, strategic alignment, etc. 4) Timeline and price: Outline the project timeline and provide an overall pricing estimate based on the scope of work and proposal elements. Context: The lead is looking for professional advice to address business challenges they are facing. The analysis should help formulate a detailed and actionable plan to resolve their issues. I’m a [describe your shop], and my target audience is [describe your audience] Constraints: Ensure the analysis is thorough and specific. Maintain confidentiality of the information provided in the call transcript. The scope of work should be realistic and achievable within the proposed timeline. Examples: A business struggling with declining sales despite increasing marketing spend. A company facing operational inefficiencies that have led to increased costs and reduced profitability. Do you have cool tricks you like to use your call transcripts for? Hit reply and let me know. Repost this ♻️ if you wanna help your friends 😎