No bad but there are better options elsewhere
I purchased T2 and had high hopes, but ended up not being too impressed. It wasn't that anything was especially "bad", just not as great as what's available other places.
The pros:
++ I like the UI. It's sleek and intuitive
++ I love being able to create custom agents and saving prompts (awesome time-saver when you have repeated use-cases)
++ The quality of the image and video generation was good, but then, that relies mostly on the AI and no so much on the SAAS.
The cons:
- - Credit usage (they just get eaten up as if they were free-range chickens in a fox den.)
- - document analyzer sorely lacking. The chat didn't analyze the full text, even when prompted, so this must be a limitation of Qolaba. I tested this in several ways. That would be fine as a changeable default, except there's no way to opt-in more of the doc to be sampled.
- - chat responses are inferior when analyzing info from a doc. I compared results on the same LLM and prompt on a different doc analyzer (that is currently available on Appsumo). The responses were vastly different (with Qolaba being inferior/incomplete/generic), which is odd when using the same LLM and prompt and document.
Basically, I didn't find anything special with Qolaba. As a document analyzer, there are better out there. As a one-stop shop for image generation, it's sufficient, but credit-costly. That said, three tacos because the potential is there. I mean, if the query cost was less and the doc analyzer worked well, it'd be a keeper. As it is, not so much.

Annapurna_Qolaba
Jun 27, 2025Hi there 👋
Thanks so much for your honest feedback and for giving Qolaba a spin.
You're right, credit usage can add up quickly, especially with premium models like Kling. We’re working on clearer credit guidance and making more efficient model options easier to find.
Regarding the document analyzer, this is incredibly helpful feedback. The issue you encountered is related to an ongoing upgrade of our RAG (Retrieval-Augmented Generation) system, which powers how documents are read and responded to. During this transition phase, some inconsistencies or limitations are expected, but we’re actively improving this so that Qolaba can handle larger and more complex documents more intelligently.
I’d love to follow up and understand your use cases better—feel free to hop into our Discord or grab time on my calendar if you're open to a quick chat:
🔗 Discord: https://discord.gg/63aR6qcKyc
🔗 1:1 call: https://calendly.com/annapurna-qolaba/30min
Really appreciate you taking the time to help us get better!
Annnapurna Viswanadham
Founder’s Office, Qolaba