AI platform for teams
2342.ai clears the AI subscription pile off the table.
Not another model. Not another isolated tool. 2342.ai is the operating layer in between: chat, research, images, files, RAG and an OpenAI-compatible API on one shared budget. So a team can work with AI without bolting another subscription onto every person.
We do not run our own foundation model. We build the workbench that makes several models controllable inside a company.
One workspace, not a tool zoo
AI gets expensive when every team builds its own little shelf of tools.
A team does not need private logins, scattered prompts and invoices that accounting has to decode later. It needs one workspace, clear budgets and an API that behaves like the OpenAI workflows already in place.
What matters day to day
If AI is supposed to stay inside the company, it has to be controllable.
Not with strategy slides. With daily operating questions: which teams may use which models, which access is approved, which API keys are active, and what usage sits on top of the team access fee.
SOTA models without tool sprawl
The privacy story is central access, roles, budgets and traceable usage. For the team it stays simple: one workspace, one API, clear control.
Good prompts do not belong in private notes
When a workflow works, it belongs to the team. Otherwise everyone copies half a template from some chat history and calls it process.
The task decides, not provider folklore
Some work needs a cheap model. Some needs research. Some needs image generation. Users should not have to study provider politics first.
Costs must be visible before they run away
Charts after month end are accounting, not control. What matters are limits, owners and a budget that does not fall apart across ten tool accounts.
What you get
A platform that makes sense to purchasing, IT and the teams doing the work.
One access point instead of a provider zoo
OpenAI, Anthropic, Google, Perplexity, xAI and more providers become usable through one platform. One login. One budget. One place where rules can apply.
Platform fee and usage stay separate
The plan pays for the shared access layer. Model usage stays visible as its own budget, so nobody confuses a seat fee with the real cost of the work.
Platform operation in Germany
The platform runs on our own infrastructure in Nuremberg. That does not solve every model-provider question, but it removes the application layer from the usual cloud patchwork.
OpenAI-compatible API
Existing workflows do not have to be rebuilt. Change the base URL, set the key, keep working. More like moving a cable than tearing down a wall.
Chat, research, RAG and files in one place
The workday should not jump between ten tabs. Projects, threads, storage, vector data and research belong on the same workbench.
Team access without seat penalty
When ten people work with AI, the same base fee should not be due ten times. The team grows. Fixed costs do not have to run behind it.
Standards instead of gut feeling
Good individual tricks only become a process when the team can reuse them.
A useful prompt hidden in a private chat helps exactly one person. A shared team prompt helps the whole operation. Add budgets, roles and traceable models, and AI becomes a tool. Not a foggy side project.
How rollout starts
Put order in place first. Then let usage grow.
Set the budget frame
Start with a clear monthly frame instead of five individual provider subscriptions someone has to reconcile later.
Make the team operational
Access, prompts, models and rules move into one place. No internal tool bazaar.
Watch usage
Chat, research, images and API run together. Costs stay visible before they become a month-end problem.
Pricing
Do not charge by chair when usage writes the bill.
Seat pricing looks clean while only three people are involved. Once AI spreads across departments, you suddenly pay for attendance instead of work. Our logic: a fixed platform fee for team access, a shared usage budget for model consumption, no penalty for adding another person.
Starter
25 EUR / monthFor individual users and small internal tests.
- Platform access and OpenAI-compatible API
- Model catalog across several providers
- Usage budget visible separately from access
Professional
99 EUR / monthFor teams that use AI daily, not just as an experiment.
- Team access without per-member pricing
- Shared usage budget for model consumption
- Prompt library and team functions
- Usage and budget view for owners
Enterprise
199 EUR / monthFor companies with more usage, more rules and API integration.
- Higher limits and prioritized support
- Own operating and approval processes
- Technical help for rollout, API usage and usage budgets
Questions before rollout
The hard objections belong on the table before anyone buys.
Why no seat prices?
Because AI costs are not cleanly attached to office chairs. Usage, model choice and control matter. Seat models punish growth in the wrong place.
Does 2342.ai run its own models?
No. We run the platform, API, budget logic and team controls. The models come from several providers. That is exactly why the layer in between matters.
Is this only an API or also a workspace?
Both. Developers can connect existing tools through the API. Teams can work directly with chat, research, images, files and reusable prompts.
How is this different from individual provider subscriptions?
You bundle access, costs, rules and teamwork in one place. That saves money, but also coordination, shadow processes and privacy headaches.
How does this fit GDPR and compliance work?
The platform runs on our own infrastructure in Nuremberg. The privacy lever is central access, roles, budgets and traceable usage, instead of scattered individual tool accounts.
How fast can a team start productively?
As soon as login, budget and first standards are in place. That is why we prioritize clear defaults, reusable prompts and traceable models over feature theater.
Next step