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A design and development company transforming ideas into remarkable digital products. Contact us to do your design and development work right.

With over 1000 successfully delivered projects and 200+ skilled professionals, we have worked together with multinationals like Volkswagen, unicorns like Flexport, and notable personalities like Serena Williams. We are a Y Combinator Winter 2014 company, backed by funds like Social Starts and angel investors like Pete Cashmore, founder of Mashable. This year we were also recognized as one of the top 100 highest-growing B2B service providers by Clutch. Our projects are delivered by experienced software engineers and designers and are always backed up by the best project managers and quality assurance analysts. With us, quality and deadlines are never compromised, whether it’s bringing your fresh idea to life or improving the quality of an existing project. Be it a mobile or web app, SaaS, or any other software solution, we have the skillset and expertise to turn your ideas into remarkable products.

10/16/2026

Some combinations are simply unavoidable. 🥇
Which duo do you know too well?

10/15/2026

There is a big difference between “the feature works” and “the user can complete the task.” ⚠️

Imagine a patient form where every field functions correctly, but keyboard focus jumps in the wrong order.

Or a successful submission where the status update is invisible to a screen reader.

From a functional perspective, very little is broken.
𝗙𝗿𝗼𝗺 𝘁𝗵𝗲 𝘂𝘀𝗲𝗿’𝘀 𝗽𝗲𝗿𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲, 𝘁𝗵𝗲 𝗷𝗼𝘂𝗿𝗻𝗲𝘆 𝗰𝗮𝗻 𝘀𝘁𝗼𝗽 𝗰𝗼𝗺𝗽𝗹𝗲𝘁𝗲𝗹𝘆. ⛔️

That is why accessibility belongs in QA, particularly around critical healthcare flows.

These five checks help teams look at the product from a wider perspective before release or a compliance review. ✅

10/15/2026

The QA team now has to solve an interesting problem: 𝗔𝗜 𝗵𝗲𝗹𝗽𝘀 𝘁𝗵𝗲𝗺 𝘁𝗲𝘀𝘁 𝗳𝗮𝘀𝘁𝗲𝗿 𝘄𝗵𝗶𝗹𝗲 𝗮𝗹𝘀𝗼 𝗺𝗮𝗸𝗶𝗻𝗴 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗵𝗮𝗿𝗱𝗲𝗿 𝘁𝗼 𝘁𝗲𝘀𝘁. 🔎

That is the environment Jan, our Head of QA, works in every day. 👋

Traditional features are often easier to verify because expected behaviour can be defined very precisely.

With AI, teams also need to account for variability, edge cases, changing outputs, and whether the result is useful enough across more than one successful run.

That changes the QA mindset. 🧠

Instead of treating AI as another feature type, Jan looks at how it behaves across scenarios, how failures are surfaced, how users experience the output, and whether the wider product remains accessible and reliable.

𝗔𝗜 𝗰𝗮𝗻 𝘁𝗮𝗸𝗲 𝗮 𝗹𝗼𝘁 𝗼𝗳 𝗿𝗲𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝘄𝗼𝗿𝗸 𝗼𝘂𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗽𝗿𝗼𝗰𝗲𝘀𝘀, 𝗯𝘂𝘁 𝗱𝗲𝗰𝗶𝗱𝗶𝗻𝗴 𝘄𝗵𝗮𝘁 𝗰𝗼𝘂𝗻𝘁𝘀 𝗮𝘀 𝗮𝗰𝗰𝗲𝗽𝘁𝗮𝗯𝗹𝗲 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 𝘀𝘁𝗶𝗹𝗹 𝗿𝗲𝗾𝘂𝗶𝗿𝗲𝘀 𝗮𝗻 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲𝗱 𝗤𝗔 𝗽𝗲𝗿𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲.

That combination is becoming an increasingly important part of shipping AI products with confidence.

Need QA expertise around your next release? Let’s talk 🔗 https://povio.com/lets-talk

10/14/2026

Building healthcare software for the US and Europe means working with two very different compliance frameworks. 🇺🇸🇪🇺

🟣 HIPAA focuses specifically on protected health information in the US healthcare environment.

🔵 GDPR reaches more broadly across personal data and introduces requirements around data minimisation, transparency and user rights.

For a CTO or Head of Product, that affects far more than the privacy policy. ⚠️

It can influence:
◽️ How you structure access and permissions
◽️ What data your product collects and retains
◽️ How users manage their data
◽️ What gets logged and audited
◽️ How third-party integrations are designed

These decisions are much easier to handle while the product is being built than after the architecture is already set.

With 80+ healthcare projects behind us, this is the kind of context we bring into healthcare product development. 🏆

10/13/2026

Healthcare AI becomes an engineering problem surprisingly fast. ⚠️

Once the model touches real workflows and sensitive data, product teams need more than a good prompt and a working API.

Five lessons we would take into any healthcare AI build:
1. Control what data the model can access.
2. Keep important outputs reviewable.
3. Give engineering enough visibility to investigate issues.
4. Design a safe fallback when AI cannot help.
5. Keep human judgment where the consequence is significant.

That combination of AI, product, and engineering is what turns an experiment into a healthcare product people can depend on. 🏆

10/13/2026

Healthcare products in Europe need more than strong engineering. 🏥

They need strong data practices too.

GDPR is one of the key requirements healthcare product teams need to account for when working with EU user data. 🇪🇺

We’ve worked across 80+ healthcare projects, combining product, engineering and compliance experience around sensitive data and regulated environments.

For GDPR, that means helping teams assess the current setup, define remediation, implement controls, document the process and keep compliance up to date as the product evolves. 🌟

The work is supported by certified DPO expertise and a team that understands both the legal and technical side of the product.

Building with EU user data? We’re always happy to share what we’ve learned.

10/12/2026

A big company milestone deserves a brand ready for the next one. 🌟

Knowtex was recently named one of two prime awardees on the VA’s $775.72M Ambient Scribe Enterprise contract, another major step in the company’s healthcare AI journey. 🏆

Around the same time, we helped refresh the website, social content, and visual language to better represent where the brand is heading.

But healthcare design also comes with its own rules. 🏥

For Knowtex, that means thinking carefully about clinical workflows, accessibility, clear system feedback, and consistency across the experience.

We’re now taking that thinking further with a new component and design system. 🔜

10/09/2026

Q3 performance review:
We planned. We prompted. We subscribed to another AI tool.

What does yours look like? 👀

10/07/2026

The closer AI gets to taking action, the more trust the product has to earn. 🌟

That trust comes from how the product behaves around the model:
𝟭. 𝗦𝗵𝗼𝘄 𝘄𝗵𝗲𝗻 𝗔𝗜 𝗶𝘀 𝗶𝗻𝘃𝗼𝗹𝘃𝗲𝗱
Users should know when content, recommendations, or actions are AI-generated.

𝟮. 𝗠𝗮𝗸𝗲 𝗸𝗲𝘆 𝗼𝘂𝘁𝗽𝘂𝘁𝘀 𝗲𝗮𝘀𝘆 𝘁𝗼 𝘃𝗲𝗿𝗶𝗳𝘆
Give important answers enough context, sources, or supporting data to be checked.

𝟯. 𝗞𝗲𝗲𝗽 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗮𝗰𝘁𝗶𝗼𝗻𝘀 𝘂𝗻𝗱𝗲𝗿 𝘂𝘀𝗲𝗿 𝗰𝗼𝗻𝘁𝗿𝗼𝗹
Higher-impact actions may need review or confirmation before they happen.

𝟰. 𝗠𝗮𝗸𝗲 𝗺𝗶𝘀𝘁𝗮𝗸𝗲𝘀 𝗲𝗮𝘀𝘆 𝘁𝗼 𝗰𝗼𝗿𝗿𝗲𝗰𝘁
Edit, retry, undo, or escalate. A wrong output should have a clear recovery path.

𝟱. 𝗦𝗲𝘁 𝗰𝗹𝗲𝗮𝗿 𝗯𝗼𝘂𝗻𝗱𝗮𝗿𝗶𝗲𝘀 𝗳𝗼𝗿 𝗱𝗮𝘁𝗮 𝘂𝘀𝗲
Users need to understand what the AI can access and how that information is being used.

These details shape whether people try an AI feature once or start relying on it in their workflow.

We can help product and engineering teams define those trust layers, then design, build, test, and ship the AI experience around them 🔗 https://www.povio.com/lets-talk

10/06/2026

Putting two and two together:
when senior engineers are filling delivery gaps, one team is carrying the critical work, and quality starts dropping, you probably do not have five separate problems. 🧑‍💻

You have a capacity problem starting to become a business risk. ⚠️

Here are 5 signals worth acting on before the deadline moves:

𝟭. 𝗦𝗲𝗻𝗶𝗼𝗿 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 𝘀𝘁𝗮𝗿𝘁 𝗰𝗼𝘃𝗲𝗿𝗶𝗻𝗴 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆
When your most experienced people spend more time filling ex*****on gaps, they have less room for architecture, reviews, mentoring, and the decisions only they can make.

💡 Consider 𝗮𝗱𝗱𝗶𝗻𝗴 𝘀𝗲𝗻𝗶𝗼𝗿 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗰𝗮𝗽𝗮𝗰𝗶𝘁𝘆 around the ex*****on work.

𝟮. 𝗢𝗻𝗲 𝘁𝗲𝗮𝗺 𝗰𝗮𝗿𝗿𝗶𝗲𝘀 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆
If every important release, customer commitment, or new initiative depends on the same people, one bottleneck can affect several priorities at once.

💡 Separate part of the workload or give a defined initiative its 𝗼𝘄𝗻 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆 𝘁𝗲𝗮𝗺.

𝟯. 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗱𝗿𝗼𝗽𝘀 𝘂𝗻𝗱𝗲𝗿 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆 𝗽𝗿𝗲𝘀𝘀𝘂𝗿𝗲
More bugs, rushed reviews, reduced testing, and shortcuts in the codebase are often signs the team is delivering beyond sustainable capacity.

💡 Add capacity before the trade-off between 𝘀𝗽𝗲𝗲𝗱 𝗮𝗻𝗱 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 becomes permanent.

𝟰. 𝗛𝗶𝗿𝗶𝗻𝗴 𝗰𝗮𝗻’𝘁 𝗸𝗲𝗲𝗽 𝘂𝗽 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗱𝗲𝗮𝗱𝗹𝗶𝗻𝗲
Permanent hiring can still be the right long-term plan. It just does not solve a delivery gap that exists today.

💡 Use 𝗳𝗹𝗲𝘅𝗶𝗯𝗹𝗲 𝘀𝗲𝗻𝗶𝗼𝗿 𝗰𝗮𝗽𝗮𝗰𝗶𝘁𝘆 while recruitment continues.

𝟱. 𝗡𝗲𝘄 𝗶𝗻𝗶𝘁𝗶𝗮𝘁𝗶𝘃𝗲𝘀 𝗵𝗮𝘃𝗲 𝗻𝗼 𝗼𝘄𝗻𝗲𝗿
If new work keeps entering the roadmap without someone who can fully own it, adding tasks to the existing team will only spread attention thinner.

💡 Give the initiative 𝘀𝗲𝗽𝗮𝗿𝗮𝘁𝗲 𝗼𝘄𝗻𝗲𝗿𝘀𝗵𝗶𝗽 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝗺𝗶𝘅 𝗼𝗳 𝗿𝗼𝗹𝗲𝘀.

The useful question is not always “Do we need more engineers?”
It is: 𝘄𝗵𝗲𝗿𝗲 𝗶𝘀 𝘁𝗵𝗲 𝗰𝘂𝗿𝗿𝗲𝗻𝘁 𝘁𝗲𝗮𝗺 𝘀𝘁𝗿𝗲𝘁𝗰𝗵𝗲𝗱, 𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝘁𝘆𝗽𝗲 𝗼𝗳 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝗿𝗲𝗺𝗼𝘃𝗲𝘀 𝘁𝗵𝗮𝘁 𝗽𝗿𝗲𝘀𝘀𝘂𝗿𝗲 𝗳𝗮𝘀𝘁𝗲𝘀𝘁? ✅

We can help you work through that decision first.

Our experts can look at the roadmap, team setup, deadlines, and technical gaps, then recommend whether the right move is a senior engineer, a specialist, or a dedicated delivery team.

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1390 Market Street, Suite 200
San Francisco, CA
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Monday	12am - 11:59pm
Tuesday	12am - 11:59pm
Wednesday	12am - 11:59pm
Thursday	12am - 11:59pm
Friday	12am - 11:59pm
Saturday	12am - 11:59pm
Sunday	12am - 11:59pm

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http://povio.com/

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