any tech is a boutique for specialized development and applied AI, focused on turning complex visions into high-performance systems through singular perspectives and cutting-edge technology.
Seven moments in 49 years. Companies that became benchmarks were founded in every one of them. The ones that waited for things to mature spent the years after explaining why.
1977 → 2026
1977Apple Computer Co. is founded by two guys in a garage. Microsoft is 2 years old. Oracle will be founded within 12 months. The ones who jumped in early became trillionaires. The ones who said "it's a toy" became footnotes.
1981IBM launches the PC. Bill Gates licenses DOS for a royalty, not a sale. For 15 years, every PC sold pays Microsoft. The most profitable contract in history. Business vision beats product vision.
1991The World Wide Web goes live at CERN. Foundation laid. Within 36 months Jeff Bezos walks away from Wall Street to sell books online. Yang & Filo build Yahoo in their dorm room. The window took 3 years to become obvious. For them, it was early.
1995Wang Laboratories ($3 billion in revenue in 1985, the "serious company" of its industry) files for bankruptcy after ignoring the PC. Netscape goes public the same year and proves it: software scales like no business before it. The difference was not technology. It was the timing of a decision.
2007The iPhone launches. Within 36 months come Uber (2009), Airbnb (2008), Instagram (2010), WhatsApp (2009). Every one became a unicorn. Every one only existed because someone looked at the iPhone and saw a business, while Nokia still thought it was "just a phone."
2022OpenAI reaches $1 billion in annual revenue in 18 months, an all-time record in SaaS history. Anthropic, Cursor, Perplexity and Midjourney explode in its wake. Each is worth billions today. Each was founded by people who saw it before it made headlines.
2026Multi-agent systems in production. AI does not answer, AI executes. The next Apple, Microsoft and Amazon are being founded right now, in this window. So is the next Wang Laboratories. It just does not know it yet.
Apple. Microsoft. Amazon. Google. OpenAI. Every one was founded by people who recognized the window before it became obvious. The next list of benchmark companies is being written now: in AI, in agents, in autonomous systems. The question is not whether it will happen. It is who will be on it.
↓ continueSeven moments in 49 years. Companies that became benchmarks were founded in every one of them. The ones that waited for things to mature spent the years after explaining why.
→ scroll to beginApple Computer Co. is founded by two guys in a garage. Microsoft is 2 years old. Oracle will be founded within 12 months. The ones who jumped in early became trillionaires. The ones who said "it's a toy" became footnotes.
IBM launches the PC. Bill Gates licenses DOS for a royalty, not a sale. For 15 years, every PC sold pays Microsoft. The most profitable contract in history. Business vision beats product vision.
The World Wide Web goes live at CERN. Foundation laid. Within 36 months Jeff Bezos walks away from Wall Street to sell books online. Yang & Filo build Yahoo in their dorm room. The window took 3 years to become obvious. For them, it was early.
Wang Laboratories ($3 billion in revenue in 1985, the "serious company" of its industry) files for bankruptcy after ignoring the PC. Netscape goes public the same year and proves it: software scales like no business before it. The difference was not technology. It was the timing of a decision.
The iPhone launches. Within 36 months come Uber (2009), Airbnb (2008), Instagram (2010), WhatsApp (2009). Every one became a unicorn. Every one only existed because someone looked at the iPhone and saw a business, while Nokia still thought it was "just a phone."
OpenAI reaches $1 billion in annual revenue in 18 months, an all-time record in SaaS history. Anthropic, Cursor, Perplexity and Midjourney explode in its wake. Each is worth billions today. Each was founded by people who saw it before it made headlines.
Multi-agent systems in production. AI does not answer, AI executes. The next Apple, Microsoft and Amazon are being founded right now, in this window. So is the next Wang Laboratories. It just does not know it yet.
Apple. Microsoft. Amazon. Google. OpenAI. Every one was founded by people who recognized the window before it became obvious. The next list of benchmark companies is being written now: in AI, in agents, in autonomous systems. The question is not whether it will happen. It is who will be on it.
↓ continueWe are any tech, an artificial intelligence engineering boutique. We are not a volume consultancy or a prototype factory: we work with a select few companies per cycle, building autonomous systems for problems generic technology cannot solve.
Every project is treated as an author's work: designed, written and audited by senior engineers, from the first commit to the last deploy.
Artificial intelligence only matters when it holds up as serious software. We design every system to survive real production, not to impress in a demo.
We build autonomous agents, reasoning pipelines and critical infrastructure. We do not sell prompt wrappers; we deliver software that operates on its own and creates measurable consequences.
We take on a limited number of partners per cycle because we treat every engagement as a singular work. No handoffs, no outsourcing, no juniors learning on the client's dime.
If you recognized your company in the left column, there's no shame in it. Almost everyone is there. But the playbook that gets you out is not the one that got you here.
Dive in and explore a few of our cases.
01 / 05How we built an agent that turns plain-language questions into SQL, runs them on the database and analyzes the results in Python, removing the data analyst bottleneck.
2026 · Healthcare · Data Science · May 2025 → ongoing
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02 / 05How we built an agentic document search system for a public health institution: no vector store, BM25, and metadata governance that answers what embeddings never could.
2026 · Healthcare · Quality Management · Q4 2025 → Q2 2026
View details03 / 05How we built four specialist agents, each isolated in its own microservice, with node-by-node SSE streaming and role-based access control for a public healthcare institution.
2026 · Healthcare · Hospital Operations · May 2025 → ongoing
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04 / 05A platform that transcribes consultations, extracts clinical data with AI, and turns it into epidemiological dashboards for healthcare networks.
2026 · Healthcare · Telemedicine · 2025 → ongoing
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05 / 05How we modeled radiology no-show risk at a major public hospital, reaching ROC-AUC 0.78 under strict temporal validation, and what the data revealed about patients.
2026 · Healthcare · Data Science · 2026 → ongoing
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Where we keep the work. Dive in and explore a few of our cases: systems, products and experiments, all shipped.
Enter the archive01 / 05How we built an agent that turns plain-language questions into SQL, runs them on the database and analyzes the results in Python, removing the data analyst bottleneck.
Own product · ANy tech · 2026 · Healthcare · Data Science · May 2025 → ongoing
02 / 05How we built an agentic document search system for a public health institution: no vector store, BM25, and metadata governance that answers what embeddings never could.
Own product · ANy tech · 2026 · Healthcare · Quality Management · Q4 2025 → Q2 2026
03 / 05How we built four specialist agents, each isolated in its own microservice, with node-by-node SSE streaming and role-based access control for a public healthcare institution.
Own product · ANy tech · 2026 · Healthcare · Hospital Operations · May 2025 → ongoing
04 / 05A platform that transcribes consultations, extracts clinical data with AI, and turns it into epidemiological dashboards for healthcare networks.
Own product · ANy tech · 2026 · Healthcare · Telemedicine · 2025 → ongoing
05 / 05How we modeled radiology no-show risk at a major public hospital, reaching ROC-AUC 0.78 under strict temporal validation, and what the data revealed about patients.
Own product · ANy tech · 2026 · Healthcare · Data Science · 2026 → ongoing
Interviews with leaders, a close read of processes, a close read of data. Before we propose anything, we learn the terrain.
Technical feasibility, estimated costs, projected ROI, dependencies. A document that holds up a decision.
Architecture, code, integrations, tests. A senior team inside the project. Short iterations with you in the loop.
A documented handover. You walk away with the system, the code, the architecture and the autonomy. No lock-in.
The eight disciplines we have mastered, gathered into four lines of work. Each one backed by delivered cases, a documented methodology and a senior lead on our side.
Teams of specialized agents with orchestration, shared memory and human review, automating repetitive administrative work from end to end.
View service→Knowledge bases that cite their sources and govern access by role, paired with predictive models that run as living systems, not as notebooks.
View service→Software built from scratch when nothing that exists will do, on top of data lakes, pipelines and access layers designed to keep agents running 24/7.
View service→Data protection, usage policies, access control and auditing, plus team training so AI actually reaches the shop floor.
View all services→Tell us the problem. Within 48 hours we come back with a point of view. If it's worth pursuing, we keep going. If not, at least you walk away with clarity.