AI that works on your data — and keeps it yours.
We design and build private AI gateways, AI data analysts, and AI features for web and mobile products.
- Fixed price per phaseno surprise invoices
- You own the codeonce the phase is paid
- Quality measured before launchagreed evaluation set
- Your data never trains modelsno-training settings
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What we build
Every engagement starts with a fixed scope and price. Cloud, model API, and GPU costs are billed at cost or paid by you directly.
AI Readiness Sprint
Find where AI pays off: process map, data readiness check, 3–5 ranked use cases and a pilot plan with one success metric.
Private AI Gateway
One controlled entry point to cloud models. Personal and confidential data is masked before it leaves your network.
AI Data Analyst
Ask your data warehouse questions in plain English. Answers come with the chart and the query, access rights respected.
AI Features in Your Product
Assistants, search, and copilots inside your app, each shipped with an evaluation set and cost limits.
AI Agent for One Process
Automate one workflow end to end, such as lead triage, support replies, or document intake, with a human approving key steps.
Web & Mobile Development
MVPs and production apps for iOS, Android, and web, built AI-ready: design, backend, QA.
How the gateway works
Four of the five steps happen inside your network. Only masked text crosses the boundary.
- 01 DETECT
Find sensitive values
Rules and a local model find names, emails, card and account numbers, keys, and your own identifiers.
inside your network - 02 MASK
Replace them
Each value becomes a placeholder like [PERSON_1]. The same value always gets the same placeholder.
inside your network - 03 ROUTE
Send to the right model
Cloud model, local model, or blocked, chosen by policy, team budget, and the type of data found.
crosses the boundary - 04 LOG
Record the request
Who asked, which model answered, what was masked. The audit log stays with you.
inside your network - 05 RESTORE
Put values back
The reply comes back with real values restored, so people work with the actual names and numbers.
inside your network
How we work
You can stop after any phase and keep everything built so far.
- 2 weeks · fixed
Readiness Sprint
We find the use case worth building and agree on how success will be measured.
- 2–4 weeks
Prototype on your data
A working version on a sample of your data, measured against the agreed target.
- 4–10 weeks
Production
Security, integrations, monitoring, and handover to your team.
- monthly · optional
Run and improve
Evaluation runs, model updates, and cost tuning as usage grows.
What you can hold us to
- Your data never trains models. We don't use client data for training and configure providers with no-training and zero-retention options where they offer them.
- Deploy where you choose. Your cloud account, your servers, or a mix of both.
- You own the code. Code, prompts, evaluation sets, and configuration are yours once the phase is paid.
- Quality is measured. We agree on an evaluation set before building and launch when it passes.
- Fixed price per phase. Scope and price are agreed before each phase starts. No surprise invoices.
What we build with
We pick per project and explain why. Nothing here locks you into a platform of ours.
Models
Cloud models through their APIs, and open-weight models (Llama, Qwen, and Mistral) on your hardware.
AI engineering
Retrieval (RAG), text-to-SQL, agents with tool use, evaluation sets, guardrails, cost limits.
Data
PostgreSQL, BigQuery, Snowflake, and ClickHouse, with pipelines from CRM, billing, and product databases.
Apps
React, Next.js, React Native, Swift, and Kotlin, with Node.js and Python backends.
Questions we get first
Where does our data go?
With a gateway in place, every prompt passes through a component running in your network first. Personal and confidential values are replaced with placeholders before anything is sent to a cloud model, and the originals never leave your infrastructure. For fully private setups we run open-weight models on your own servers, so nothing goes to a third party.
Do you train models on our data?
No. We don't use client data to train models, and we configure model providers with no-training and zero-retention options where they offer them. If a project needs fine-tuning, it runs on your infrastructure and the result belongs to you.
Can everything run on our own servers?
Yes. We deploy open-weight models on your hardware or in your private cloud account. In the Readiness Sprint we size the hardware and show where a local model is good enough and where a cloud model is worth it.
Who owns the code?
You do. Code, prompts, evaluation sets, and configuration transfer to you once the phase they belong to is paid. Nothing depends on a platform of ours.
How do payments work?
The Readiness Sprint is paid before kickoff. Fixed-price projects are invoiced per milestone before it starts. Hourly work is invoiced monthly for hours actually spent. All invoices are in US dollars. Cloud, model API, and GPU costs are billed at cost or paid by you directly.
What if the prototype misses the target?
The target and the evaluation set are agreed before we build. If the prototype doesn't reach it, you decide: adjust the scope, try a different approach, or stop. You keep everything built so far, and the next phase never starts without your approval.
Tell us which process you want to change.
A 30-minute call is enough to tell whether AI fits, what it would cost, and where to start. We reply within one business day.