r/productreview

Does CHAI actually remember things between conversations or does it reset every time? That's my main dealbreaker with most of these apps.

Also curious how customizable the personality is. Some of them let you shape it quite a bit and others are pretty rigid.

Our team has been going back and forth on whether to adopt Heidi Health and I'm trying to gather as much real world feedback as possible before we make a decision.

The marketing materials are polished but I've been burned before by tools that looked great in a trial and fell apart in actual use. Specifically I'm wondering about the accuracy of clinical note generation, how it handles edge cases, what the support is like when something goes wrong, and whether the pricing makes sense at scale.

If you've been using it for a few months or longer, your perspective would be really valuable. Both the good and the not so good.

Character AI review, does it really work anymore or is it just broken? I have been using it for a while now, but lately it feels like the platform is just getting worse instead of better. Every time I try to get into a decent roleplay, the filters jump in and kill the vibe, and the bot memory has gotten so terrible that they forget who you are halfway through a conversation.

I keep seeing people talking about alternatives like Kindroid or Janitor AI because they supposedly handle memory and creative freedom a lot better. I was even wondering if paying for the c ai plus subscription would fix any of these issues, but most people online say it is basically a waste of money since the core problems are still there.

I really just want a chatbot that can hold a coherent storyline without losing context or triggering false alarms every two seconds. Has anyone else been dealing with these same issues, or have you actually found a workaround that makes character ai usable again?

We're currently using a different tool for clinical documentation and considering switching to ClinicFrame. Before we go through the hassle of migrating, I want to hear from people who've actually made a similar switch.

What made you choose it and has it lived up to expectations? Would you make the same decision again?

I keep seeing people talk about it everywhere as the ultimate alternative to character ai, but I am still trying to figure out if it is actually good or just riding a wave of popularity. I tried looking for the app on my phone, but I heard that any app claiming to be janitor in the app store is a total scam since the real platform is entirely web based.

I am really curious about the lack of content filters and how well their proprietary jllm holds up during long roleplays. At the same time, I see a ton of debates online regarding data privacy and whether your private chat logs are actually secure or getting leaked somewhere. I do not want to set up an account if my information is going to get compromised or if the site is constantly going to be down for maintenance.

Has anyone here been using Janitor AI for a while, and does it genuinely feel better than the other roleplay sites out there right now?

Softstar Shoes are the ugliest shoes I own, and also the most comfortable. The leather is buttery soft, and the toe box is so wide my toes have complete freedom.

Because there is no structure to the shoe, it literally feels like wearing a leather glove on your foot. The downside, aside from the elf shoe look, is the price and the fact that the thin leather can wear out quickly if you scuff it.

If you have foot pain and don't care what anyone thinks of your footwear, buy Softstars.

My current chair cost around $400 and looked solid when i got it. three years in the lumbar support has gone completely soft, the recline clicks and sticks, and the seat foam compressed so much I can feel the hard pan underneath. nothing visibly broke, the support just degraded until it stopped doing its job.
thats the problem with mid-range chairs. they do not fail catastrophically, they just slowly stop supporting you and by the time you notice you have been compensating with garbage posture for months.
the BIFL bracket has Steelcase and HM which last a decade plus. below that its disposable Amazon stuff. but the $400-700 range is this weird dead zone where everything LOOKS durable but the internal mechanics seem designed to last maybe one warranty cycle.
I sit 6-8 hours a day and replacing a chair every 3 years is not BIFL, that is just slower consumption. I came across a Kickstarter project (lavenne r9 pro) that is trying to move away from fixed lumbar toward dynamic back support that adjusts as you shift. no idea if the long term reliability holds up, and crowdfunding a chair is its own risk, but at least the design philosophy targets the right problem.
is the only real BIFL answer to just hunt down a used Leap or Aeron and accept that mid-range will never get there

Origo Shoes caught my eye because they look like classic leather sneakers. I wanted a barefoot shoe I could wear with chinos to the office.

The design is great and the toe box is wide, but the leather was surprisingly stiff when I first got them. It took a solid month of wear before they stopped feeling rigid where the shoe bends near the toes.

Now that they are broken in, they are very comfortable, but be prepared for a break in period that you don't usually get with softer barefoot brands.

Has anyone used OpenEvidence in a real clinical environment? I'm not looking for the sales pitch, just want to know if it actually does what it claims and whether the team found it useful after the first month.

Any red flags or things you wish you'd known before signing up?

I’m considering it as a way to get more practical experience before applying for investment roles, but most of what I’m finding online feels pretty promotional. Do they lay out what's expected week after week and what sort of training is included?

any real reviews? only looking for people that have gone through the 8-week course, not speculators.

I keep seeing Doximity mentioned in clinical AI discussions but I haven't found many detailed reviews from practitioners who've actually integrated it into their workflow.

Most of what I find online reads like it was written by someone who tried it for a week. Looking for people who've used it long enough to have a real opinion. What do you actually think of it after the honeymoon period?

I’m currently building a probabilistic AI agent to detect fake reviews for a project, looking at signals like account age, posting frequency, and brand concentration.

Positive fake reviews usually leave fairly clear statistical footprints (high frequency, unverified purchases, single-seller focus). However, competitor negative review attacks seem much harder to catch automatically because bad actors often buy cheap items to get "Verified Purchase" badges or use aged accounts to bypass standard filters.

For anyone who has dealt with listing attacks: What subtle patterns or behaviors usually give away a targeted negative review attack versus a genuinely unhappy customer? Is there a specific signal you’ve noticed that automated filters usually miss?

Two questions for people who've been on Avalanche a while.

First, the rebrand. When Trader Joe became LFJ, threads here suggested part of the community felt the name undercut the platform's credibility. From the outside though, usage seems to have carried on fine. Did the rebrand actually change how much you use or trust it, or was that all noise?

Second, the tech. The Liquidity Book model promises zero slippage within a price bin, with total fees running 0.01% to 0.8% including the surge component (checked July 2026). Is the zero-slippage behavior actually noticeable on mid-size swaps in practice, or only in theory?

For context they've had a decent track record on incidents too, the November 2023 front-end breach via a third-party analytics plugin got handled with about $87K compensated to affected users.

Hi all! Wanted to share my first try of Javvy protein coffee. Mind you, this is my first time trying protein coffee, so I didn't know what to expect. I ordered online from their site, got the original and caramel flavor. They sent me 2 packs of original instead, so I requested replacement. Their customer service was pretty responsive and I received my replacement after 2 days.
It was easy to make, I mixed it with almond milk + ice. Easy to blend and has a thinner consistency compared to a regular protein shake..more like ice coffee consistency. Taste-wise it has a very strong coffee flavor, similar to ice coffee latte, which I usually like.
The caramel one is too sweet for me, I prefer the original. I think I can also try mixing in banana or oats with the original to make it more filling. I think it's an easy, good protein addition that I can quickly prepare in the morning when I'm in a rush.

Does anyone have any more recommendations for similar protein drinks? I'm quite bored of my usual protein shake. Any recipes you think I should try?

Genuinely curious what people think of Upheal. I've seen it come up a few times but the reviews I find are either glowing or vague. Looking for something in between from someone who uses it regularly.

This dropshipping store is being run by Morgan Matthews, who is known for multiple previous scams.

The moment you buy they're not gonna ship you your product and will go on to buy fake reviews on Trustpilot to improve his rating.

If you actually check on the UK government website, the company is dissolved so you are buying from a company that does NOT exist

Avoid at all costs!

Quick one for Polygon traders. QuickSwap threads keep showing the same pattern: swaps failing over and over until someone raises slippage to 6 or 7 percent, and it almost always turns out the token has a transfer tax the default slippage can't absorb.

The DEX itself is fine on fees (0.3% V2, 0.01% to 1.5% tiers on V3, no protocol fee currently as of July 2026), this is purely a token-side issue.

Does anyone have a clean workflow for spotting fee-on-transfer tokens before the first failed attempt? Explorer contract reading works but is tedious. Interested in what tools people actually use day to day rather than what guides recommend.