We build the custom AI system your business needs, the core product or the automation, and deploy it on your cloud (AWS, GCP, or Azure) or your own on-prem hardware. Your data never leaves your environment, and we have delivered systems like this for enterprises before.
What we build
These are the patterns enterprises in finance, FMCG, e-commerce, SaaS, and manufacturing put into production with us. Each one is built end to end and deployed on the client's own infrastructure, whatever it is: their cloud or their on-prem hardware, shaped to their data.
What you get: your own ChatGPT-style platform, your data, your keys.
Your people get a private, ChatGPT-style assistant that runs on your own infrastructure, your cloud (AWS, GCP, or Azure) or your on-prem hardware, and answers from your data, never a shared vendor cloud. Your existing applications, any stack, connect to it through a standard, OpenAI-compatible API, so adoption is a config change, not a rebuild. Open-source models are chosen by comparative testing on your own data, and access control, usage logging, and monitoring come built in.
What you get: a team of AI agents that runs a full workflow across your systems, validates its own work, and stops for your approval at the decisions that matter.
A multi-step process that today moves by hand from one tool to the next now runs from start to finish across your CRM, ERP, email, and internal apps. An orchestrator agent plans the work and hands each part to a specialist agent that is good at one job, and the system keeps a plan, act, check, and correct cycle going until the goal is actually met. Before any action commits, a guardian check validates it against your own rules, so nothing off-policy goes out, and the agents still stop for your approval at the decisions that matter. Every step is logged and reversible, so you get a whole process handled reliably without giving up oversight.
What you get: a RAG knowledge assistant that cites its sources.
Your teams ask questions in plain language and get sourced answers from your own documents, procedures, and archives the same afternoon, plus natural-language access to your databases without writing SQL. Every answer cites where it came from, and when the system does not know, it says so instead of guessing.
What you get: agents that read documents, extract data, and report.
The repetitive work that ties up your team, reading documents, pulling out structured data, compiling reports, keeping multilingual knowledge bases current, runs on its own through AI agents that coordinate across your systems. You keep the oversight and the approval points; the agents handle the volume.
What you get: AI-driven FinOps that flags spend before it lands on the invoice.
You see a cost anomaly across AWS, Azure, and GCP within days of it starting, not when the invoice arrives, with the spike already attributed to the service that caused it. Your infrastructure gets scored for quality, and your leadership gets a written executive summary automatically. This ships as a production system that keeps running, not a dashboard that goes stale after a quarter.
How we work
Phase 01
A structured two days with your process owners.
You walk away with prioritized use cases, a capacity plan sized for your own infrastructure, and a phased roadmap you can act on, whether or not you continue with us.
Phase 02
The foundation goes up on your own infrastructure and your first use case goes live at pilot scope, with real data and real users.
You walk away with a working system measured against the acceptance criteria you agreed to, not a slide deck.
Phase 03
More use cases on the same foundation, each one delivered as its own phase with its own result.
The decision to continue is always yours, and every phase closes with something running in production.
Fixed-price phases. No long lock-ins, no vendor trap. You keep full knowledge transfer at the end, documentation and training, no black boxes.
Selected work
Client names are withheld by agreement. These are the same engagements we walk through in proposals, each one built on the client's own infrastructure.
01
A Türkiye-based global beverage producer
Automated cost monitoring across AWS, Azure, and GCP: anomaly detection with service-level spike attribution, a cross-cloud unification layer, daily email and Microsoft Teams alerts, and Power BI reporting. In production, surfacing cost spikes within 1 to 3 days instead of at month-end.
02
A digital mental-wellbeing product company
A production conversational AI for mental wellbeing, built on the client's own AWS cloud, that delivers clinically-informed, therapeutic-style support through a guided vent, reflect, reframe flow. A conductor agent routes each exchange and directs specialized agents for category detection, conversation phase, emotion, and CBT pattern recognition, with the blocking response path kept separate from background analysis so the user never waits. A two-tier safety layer screens every message and routes at-risk users to professional crisis resources in under 850 milliseconds, while the response itself streams word by word with a first token in roughly 1.9 seconds. Model selection delivered 100% reliable structured output for the detection agents and prompt caching brought LLM running cost down by about 90%.
03
A commercial construction subcontractor
When a new project goes out to tender, the client's estimators were opening every architectural PDF by hand to decide bid or no-bid, so strong projects slipped past and time went to poor-fit ones. We built a pipeline on the client's own Google Cloud that reads each project's plans, including image-based title blocks, with OCR and an LLM extraction step, pulls out square footage, owner, and building type, and turns mixed image-and-text plans into one bid-fit confidence score, so the team only chases the projects worth their time. A secure web app lets estimators tune the scoring and capture feedback, and that feedback sharpens future scores.
Our products
Our flagship product runs on the same privacy-first architecture we deliver to consulting clients. The agent runs in your own cloud and your prospect data never leaves your environment; our central intelligence API sends back only researched, scored leads.
How it works
WK 01
You define your ideal customer profile and what counts as a qualified meeting.
WK 02
The agent is set up inside your own AWS, GCP, or Azure account.
WK 03
Nothing goes out until you have reviewed and approved the outreach.
WK 04
Researched, scored leads and a short report, on your desk every Monday.
We also run a specialized AI security-testing service for your externally facing AI systems.
Quality & evaluation
Shipping untested AI is like manufacturing without quality control.
Every system you receive from us comes with scenario-based test sets, measured accuracy and hallucination rates, and acceptance criteria agreed before go-live. The quality bar is not a promise, it is a number you sign off on.
Common questions
About
Founder · AI Architect · Istanbul
Burcin is an AI engineer with 10+ years across machine learning, NLP, and LLM systems, and the founder of CCB AI Solutions, an enterprise AI consultancy based in Istanbul, Turkey.
He has delivered tailored AI Products for clients across Europe, MENA, and the US, and is a member of the Toptal network.
US invoicing available
Book a free 30-minute consultation, whether that is a private LLM platform in your own cloud, a specific automation you want off your team's plate, or our lead-generation product. No pitch deck, no pressure, and we reply within one business day.
or write directly: info@ccb-ai.com
