We unlock 1337 in you.
BiggeorGe
Who we work with: KAVOSZ, BiggeorGe, Yettel, Dorsum, Finshape.
“1337 Partners is the reliable partner that brought state-of-the-art technology and a real understanding of large enterprises at the same time, in the field of AI agents.”
01 · 1337 AI
1337 AI is the intelligence layer between your existing data systems (core, ERP, DMS, CRM, M365) and any AI model. It builds knowledge from your internal systems, keeps the data in-house, and we roll it out so your teams actually use it.
02 · Rollout
That is why the platform comes with engineers: they sit in your team, work on live data, and stay until the system runs in production.
From interviews and process data we rank your use cases. Every one starts with an ROI estimate.
We integrate 1337 AI with your systems and build AI workflows on your own data.
We train your key people and keep measuring the impact.
Every use case starts with an ROI estimate.
You see a working version every week, and feedback lands on that.
You move on when the previous phase hit the numbers it promised.
| License only | Built in-house | 1337 | |
|---|---|---|---|
| First production use case | You have the license, the rollout is on you. | Depends on your own team's capacity. | Within 6 weeks, inside your team. |
| Data under banking secrecy | Mostly runs in the cloud. | On-prem, if you build and run it. | On-prem only. |
| Pricing | Per user or in credits. | Build, operations and API fees. | A fixed license fee for the term. |
| Exit | On the vendor's terms. | Yours, maintenance included. | Open formats, exit plan. |
| Training and adoption | Self-service. | A separate project. | Built in, on your own use cases. |
Training for your team
We train teams on their own use cases and measure adoption.
Assessment, 3 days on-site, then mentoring on your own codebase. We measure lead time before and after.
Experience first, theory after: the first working agent ships during the workshop.
12 weeks, 12-15 people trained in depth, and they teach the rest of the organization, with measured adoption.
When we're successful, your team keeps going on its own.
Trust
1997 → 2026
In 1997, most large companies had little more than a homepage. A few were already rebuilding their operations around the internet: IBM launched its e-business campaign that year, and Dell was selling more than a million dollars a day online.
AI now gives enterprises the same opening: new markets, improving EBITDA and new revenue streams. Getting there means rebuilding the organization itself, on a foundation that scales and stays secure.
We bring the platform, and the team that takes it live with you.
The icons are drawn in code on a 1-bit pixel grid, like the early Macintosh icons. On the 1997 grid, 2 dots in 100 are purple: that was the share of people online back then (Internet World Stats).
Team
The core of this team digitized a bank from the inside and shipped products in regulated environments. We know the compliance side and the operations side.
In public
We document what we build and test on LinkedIn, as we go. Mostly in Hungarian, because that's the market we work in.
“A new species has appeared all over the world. Its name is Homo agenticus: the everyday person who builds. They see a problem, open their laptop, and fix it.”Kószó Kamill · July 2026 Read on LinkedIn →
“I summed up the state of AI transformation for 2026 in 5 theses: the perception gap, the adaptation gap, the management gap, the funding gap and the compute gap.”Pereczes János · June 2026 Read on LinkedIn →
“My speech was built around a single number: 1440. That's how many minutes there are in a day, and it's up to us how we spend them.”Szilágyi Benedek · July 2026 Read on LinkedIn →
New posts from the team every week. follow 1337 Partners on LinkedIn
Careers
We look for builders who take AI live inside a bank, and pass the audit with it.
We are an AI-first company with a core team of 8–10. Constant internal learning, a high-agency culture and maximum context, without bureaucracy.
Half consultant, half architect: you take AI from discovery to production at banks and enterprises. Budapest.
Full description + apply → Pay band: HUF 1.2–2.5M gross per month + variable, ESOP after 6–12 months (per the Notion job post)You build the platform every 1337 delivery runs on: permissions, the audit trail, and model routing across cloud and on-prem. Budapest, hybrid, reporting to the CTO.
Full description + apply →If you have built something real with AI, apply even if you don't tick every box.
Why 1337
That's the level we bring out in our clients' teams. The company name is a promise: we unlock 1337 in you.
Or write directly: janos@1337.partners
A first call, a two-week assessment, and within six weeks your first use case runs in production on your own AI platform.
At the end of the two weeks you hold:
If it starts, your first use case runs in production on your own AI platform within six weeks.
What the price is made of: a fixed monthly platform license by hosting tier, a fixed-price rollout and pre-agreed engineering packages.
Forward Deployed Engineer and Software Engineer roles, plus a project-based builder network, with live AI projects at banks and enterprises.
We will get back to you with a time slot.
