Ideator - great for storyboarding, something which seems very obvious but it's very easy to miss crucial requirements while focusing on something else.

Expand - great for when you have to do a deep dive on a specific subject and English is not your first language

Evidence - perfect for responses with tight word limit - you can get the essence of your example without losing the most effective bits Review collected by and hosted on G2.com.

I would like the search feature to go through my previous sessions, so I can easily find something that I already asked about - which will minimize the amount of AI queries and therefore minimize the enviromental impact. Review collected by and hosted on G2.com.

What I like best about AutogenAI is that it genuinely supports the bid writing process rather than feeling like a generic AI tool. It is particularly useful when working with large volumes of tender information, technical input and strict response requirements, as it helps turn complex content into clear, structured and client-focused responses.

From a day-to-day user perspective, the interface is straightforward and easy to navigate. The workflow feels logical, which is important in a bid environment where time is often limited and users need to move quickly between prompts, drafts and refinements. It helps reduce the time spent starting from a blank page and gives a strong first draft that can then be shaped with project-specific detail, evidence and commercial insight.

The AI capability is valuable because it helps improve structure, clarity and consistency. For example, when developing responses around mobilisation, compliance, innovation, asset management or service delivery, it can help frame the answer properly, reduce duplication and keep the response aligned to the question. It is also useful for tightening wording where there are strict word or page limits.

From a performance and ROI perspective, the main benefit is time saving. It speeds up early drafting, helps organise content more efficiently and allows more time to be spent on adding quality, evidence and client-specific detail. That is where the value comes from, because it supports both productivity and response quality.

The onboarding and support have also been helpful, particularly in understanding how to get the best out of the tool rather than just using it for basic drafting. An unexpected benefit is that it can challenge the way a response is written by highlighting where the message could be clearer, more concise or more benefit-led. Overall, it has improved my workflow by making tender response development quicker, more consistent and easier to manage. Review collected by and hosted on G2.com.

What I dislike about AutogenAI is not so much a major issue with the platform, but more that it still requires careful review and human judgment to get the best outcome. The first draft can be useful, but it sometimes needs significant tailoring to make sure the response is fully aligned to the client’s question, the evaluation criteria and the specific operational solution being proposed.

At times, the wording can feel slightly generic if the right information is not provided upfront. In a tender environment, this means the user still needs to add contract-specific evidence, case studies, commercial detail, local delivery information and proof points to make the response credible. It is not a replacement for bid strategy or subject matter expertise.

There can also be occasions where the content needs tightening to meet strict word counts or page limits. The tool is helpful for structure and clarity, but it can sometimes produce more wording than required, so additional editing is needed to make the final response concise and focused.

From a workflow perspective, the value depends heavily on how well the source material, prompts and inputs are prepared. If the input is too broad or unclear, the output can require more refinement. I would also like to see even stronger integration with approved bid libraries, case studies, pricing assumptions and contract-specific data, as that would make the outputs even more tailored and reduce manual checking.

Overall, I see AutogenAI as a strong support tool, but it still needs experienced users to review, challenge and shape the content so that it is accurate, specific and genuinely client-focused. Review collected by and hosted on G2.com.

The integration with SharePoint, Microsoft Word, and the unlimited customer service and support to get fully implemented and educate entire teams on how to use the platform. The customer support is absolutely amazing. Review collected by and hosted on G2.com.

Sometimes the output seems a bit clunky, and there is a lack of contextual intuitive questions after a prompt to help a user dive deeper or incorporate different/missed aspects of the original question/prompt. Review collected by and hosted on G2.com.

- Ability to select Libraries and control the sources

- Ability to create targeted RFP deliverables

- User interface was consistent with other AI apps

- Performance was acceptable Review collected by and hosted on G2.com.

UI was pretty good but has opportunities for improvement with respect to finding certain functionality such as the ability to export output to a Word document Review collected by and hosted on G2.com.

I like how the interface is integrated with bids in mind. With other AI tools, there may be the same functionality but it needs to be accessed separately and isn't targeted for bids. Review collected by and hosted on G2.com.

At the moment we don't have the document library set up so I haven't been able to take full advantage of the features. Review collected by and hosted on G2.com.

I really appreciate the integration of local and global intellectual capital repositories within the library, together with the solution design workflow embedded into the user interface via Projects, and the capability to expand teamwork both in content creation (Project) and in content review (Porject). AI specialization from analysis to review is helpful, supported by some custom prompting to generate storyboard parts. I've also interacted with AutogenAI Support Team, issuing some tickets, and I promptly received feedback and resolution. I've experienced a performance boost in my traditional scavenging approach to find good intellectual capital reusable content thanks to Research, and I appreciated the Ideator feature. I used a lot the Editor We Will, Explain How, Add Case Study and Add Statistics functions, powered by company's repos are strong improver of generated content. The capability to sub-set the IC repos by Source Provider feature is also great, because you can taylor your content according to market segment, year, or specific artifact type, at least if the IC repos are well setup.

For example:

I use Extract to collect info from specific topics that could be spread into several requirement documents

I use Ideator to craft ideas turning on all the AI embedded in AutogenAI; useful ideas are converted into Drafts documents, to be used as valuable insert into a proposal document

If some diagrams are included in the document set, I analyse them using Copilot or ChatGPT, obtaining a text description of the diagram, being an org model, a high-level plan, an AOD, or similar. This enable AutogenAI to enrich its AI Analysis using content it can actually process

I use Search function within AutogenAI to look for interesting artifacts or IC that could be reused, when targeted by Sources selection within AutogenAI

I craft a prompt in Research to build prompts for REQUIREMENTS section in storyboard that are not autogenerated by AI Analysis in Project, due to custom build of proposal outline

I draft the Q&A questions list to be submitted to the Customer, together with engagement team, and generate an answer using Workbooks and Library AI; this is not intended to be meaningful to some questions, but it has proven to be informative before actual Customer answers.

I build the proposal draft within AutogenAI supported by fellow solutioners, using their knowledge on the topic to enrich the drafting with meaningful prompts; currently AutogenAI doesn’t provide followup prompts nor in Research nor in Editor, while Copilot or ChatGPT do. I use only Library AI and Datasets, narrowed to market sector or specific topics if I know these are available in KL

I use Gamma Review to suggest compliance checks with requirements, and feasible suggestions are used within AskAI as prompts

After building a proposal draft within AutogenAI, I export it to be uploaded and shared into the engagement folder, allowing other engagement people to explore its content, and use it to craft their proposal sections content; if available from other solutioners, I add images / diagrams / tables Review collected by and hosted on G2.com.

I've no detailed insights about Pricing or ROI because it is managed globally, but I guess the time to value to create usable content is well placed. I currently don't like the Project Smart Requirements workflow, preferring the Smart Questions one, because in my experience it requires more effort to carve out some good results, and I also think that the Extract feature provides too detailed output to be effectively further reused in deeper analysis.

I don't like the Compliance Checklist because somehow it misses a lot of requirements you should comply with, while the fairly detailed Compliance Matrix misses the feedback to provide review of the content already generated. It would be really helpful if the Compliance Matrix could evaluate the content generated compared with the requirements list, and track its evolution while generating the content inside the Proposal Outline Review collected by and hosted on G2.com.

Everything being in one area and being able to use your companies best practise to develop future bids Review collected by and hosted on G2.com.

Being new to AutogenAI the changing navigation has been difficult when new functionality is introduced Review collected by and hosted on G2.com.

I like that AutogenAI is purpose‑built for bids and proposals, so it understands structures, compliance, and tone much better than generic AI tools. I also value how it turns past bids and content libraries into an active asset, using semantic search and smart reuse rather than just storing documents.

Its agentic workflow tools are another standout, because they help manage multi‑step RFP processes end‑to‑end, from structuring responses to routing drafts for input and approval. Finally, I’m impressed by the measurable impact users report, such as significantly faster drafting and higher win rates on proposals. Review collected by and hosted on G2.com.

I dislike that AutogenAI is positioned and priced very much as an enterprise tool, which makes it hard for smaller teams to justify, especially with opaque “contact us” pricing, minimum seat commitments, and extra onboarding fees. I’m also not a fan of how much manual governance is still required: users have to perform their own conflict checks, manage content freshness, and verify accuracy for complex or regulated bids, which undermines some of the promised automation. Review collected by and hosted on G2.com.

I like the transformations short cuts that are available, like the word cutting and the expanding. I also like that I can chose my source provider, which helps me to know that my response is being curated by a trust source. The customer success team has been great as well. I appreciate the monthly check ins and emails about webinars opportunities. we are still early in use, but I would says is has helped in efficiency Review collected by and hosted on G2.com.

I think some parts of the UX are still clunky, small issues like selecting text. I don't like the Ask AI bar popping up every time I select text, because it can get in the way. I don't like that the copy text feature will copy over the prompt as well. I wish I could also searched from prompts that are made in the search bar area. Review collected by and hosted on G2.com.

It helps at every step of the process. I especially like the brainstorming in Home, because it helps me get past the inertia of starting to write. The main efficiency and time-saving features I’ve used are the Workflow tool to generate a proposal outline or first draft, and, within drafts, the “add case study” and reduce word count features. Review collected by and hosted on G2.com.

The navigation takes a bit of getting used to, I was going backwards and forwards in and out of sections initially but the training was very comprehensive and I think this is more to do with me learning how to use such powerful AI, like learning to work with a new team member! Review collected by and hosted on G2.com.