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FutureIT.ai

Yazılım Ar-Ge A.Ş. · Türkiye

One engineering partner for everything you run

We design, build, secure and operate software — and we run our own AI inference capacity. Nine practices, one contract, one team that is still accountable after go-live.

01
Build
Applications, backends, integrations
02
Run
Cloud, DevOps, managed operations
03
Secure
Architecture, review, response
04
Think
AI, automation, our own inference

Capabilities

Nine practices. One accountable team.

Most companies end up with a different vendor for each layer of their stack, and every incident turns into an argument about whose fault it is. We cover the whole thing, so that argument happens in our building instead of yours.

  • We put language models and machine learning where they earn their keep — inside the workflows your team repeats a hundred times a day. Every agent we ship has a defined scope, an audit trail, and a human who can stop it.

    • Agents with tools, memory and hard policy limits
    • Retrieval over your own documents, with citations
    • Document handling and back-office automation
    • Evaluation harnesses, so quality is measured rather than assumed

AI agents

An AI agent, doing actual work

Not a chat window. A supervised worker with a queue, a policy boundary and an audit trail — the pattern we ship. Below is a running simulation of four agents processing a pipeline. Switch it to Supervised and nothing moves until you approve it.

Agent operationsdemo

Mode

Agents act within policy and log everything.

Agents

Pipeline

Inbound

  • Aurora Labs

    Queued

  • Cobalt Health

    Queued

Qualified

  • Northwind Retail

    Queued

Engaged

  • Halcyon Freight

    Queued

Closed

    Activity log

    00Processed

    00Held

    04Queued

    Simulated data. No real records and no live systems — this is the interaction model, not a dashboard.

    AI agents · demo

    Managed AI inference

    The computers your AI actually runs on

    Every AI feature you ship is, underneath, a request to a machine somewhere holding a model in memory. Most companies rent that machine from whoever is cheapest this week — and inherit their queue, their latency and their privacy policy along with it.

    In plain terms

    We own the machines. We run open-weight models on GPUs we operate, and serve them over a standard API — including as a listed provider on OpenRouter, the marketplace that routes AI traffic between providers. Point your application at our endpoint and the answer comes back from capacity we control, at a price agreed in advance.

    RouterIllustration of how a request is routed. Not live capacity data.

    Pick a workload

    Our capacity

    • 8Bfast path
    • 32Bbalanced
    • 70Bdeep

    Response

    Cost you agreed to

    Per-token pricing fixed in the contract, not repriced when demand spikes somewhere else in the world.

    Latency you own

    Dedicated capacity means your p99 is a function of your traffic, not of a stranger's batch job.

    A real data boundary

    Prompts and completions stay on named infrastructure, with retention you set rather than accept.

    No rewrite to adopt

    The API is OpenAI-compatible. For most applications, switching is a base URL and a key.

    Security

    Assume someone is already inside

    Perimeter thinking assumes attacks come from outside and stop at the wall. The ones that land arrive through a dependency nobody audited, a token that never expired, or a prompt that talked your own agent into handing over the data. We design for the breach that already happened.

    InboundContainedIllustration. Select a layer to see the controls we implement there.

    Select a layer

    How we work

    Short cycles, written decisions, no surprises at the end

    Every step below produces something you keep, whether or not you continue with us. That is deliberate: it makes leaving cheap, which is the only thing that makes staying meaningful.

    01 / 05

    Discovery

    Two weeks, fixed price. We read the code, interview the people who maintain it, and write down what is actually true — which is rarely what the documentation says.

    You keep

    • System and dependency map
    • Prioritised risk register
    • Written recommendation, including the option to do nothing

    Company

    FutureIT Yazılım Ar-Ge A.Ş.

    FutureIT is an R&D-registered software engineering company in Türkiye. We act as the engineering function for companies that need one, and as reinforcement for the ones that already have a good team and not enough of it.

    We are deliberately generalist. A company that only writes application code will hand you a security problem; one that only does infrastructure will hand you an application problem. Covering the stack end to end means those arguments happen inside our building rather than across your procurement process.

    We work in small senior teams, we write things down, and we would rather tell you a project is a bad idea in week one than in month six.

    R&D status

    As a registered Ar-Ge company we run formal research programmes alongside client delivery. The technical reporting, documentation and IP tracking that R&D incentives require are already part of how we work rather than overhead added at the end of a project.

    Legal name
    FutureIT Yazılım Ar-Ge A.Ş.
    Focus
    Software engineering · AI infrastructure · Security

    Contact

    Tell us what is broken, or what you want to build

    Write to us directly. An engineer reads it rather than a sales inbox, and you will get a straight answer about whether we are the right fit — including when we are not.

    hello@futureit.ai

    English or Turkish — both are fine.