From AI Pilots to Governed Scale

Move from AI pilots to practical, governed results. We help banks and insurers redesign work, launch trusted AI use cases, build internal capability, and create the platform foundations needed to scale with confidence.

What We Do
We help financial institutions turn AI into working business capability. From agentic process improvement and AI CoE setup to regulated workflow design and AI platform engineering, we combine strategy, design, build, governance, and delivery in one team.
What You Get
You get help solving the hard part of AI adoption: making it work in real operations. That means selecting the right use cases, redesigning workflows where AI can add value, putting controls around it, and building the setup needed to scale safely.

We enabled

non-technical AI Agent Builders

Transformed

3 Firms

to be AI Native

Built over

AI projects over 23 years

Our Clients Choose Us For

Build your own AI capability

Set up the governance, skills, and operating model to run AI internally.

We help clients create lasting capability, not just deliver one-off projects.

Improve workflows with agentic AI

Focus AI on the processes where it can create measurable value.

We redesign work so agents and copilots improve execution, not add noise.

Make AI usable in regulated work

Adoption depends on trust, clarity, and the right control points.

We design AI experiences that fit regulated workflows and real user needs.

Create the foundation to scale

Scaling AI requires more than models and pilots.

We build the platform, governance, and security layer needed for repeatable delivery.

Unlock AI Value

Redesigning Work for Measurable Value

Many organizations are experimenting with GenAI and agents, but the real challenge is not adding more AI—it is improving how work gets done. We focus on the business process itself: where decisions slow down, where handoffs create friction, and where AI can create measurable value.

We help clients redesign workflows around value generation, adoption, and governance. That includes identifying the right agentic opportunities, defining control boundaries, and implementing patterns that work in regulated environments. Where relevant, we bring in ecosystem capabilities across NVIDIA, UiPath, and voice-driven experiences powered by Respeecher.

AI CoE as a Service

Building AI capability internally is hard for mid-sized financial institutions. The challenge is not only strategy, but it is also getting the right mix of governance, design, engineering, security, and delivery expertise at the right time, without adding permanent headcount or managing multiple specialist vendors.

Our AI CoE as a Service is a fixed-price operating service delivered inside your environment. The mix of experts changes as your needs evolve—from governance and setup to use case delivery, enablement, and scale, but the commercial model stays predictable. We help establish governance, launch lighthouse use cases, and build the internal capability needed to run and scale AI over time.

Related Cases

Global Insurer AI Transformation

For a global insurer across 23 markets, we built group-wide AI governance, value tracking, technical controls, and a secure LLM platform to cut duplication, risk, and wasted spend.

Regulatory Reporting Automation

Built regulatory reporting engine for a payment giant, replacing costly manual reporting with a fully automated in-house process for compliant submissions to multiple EU regulators.

AI Experience and Platform Foundations

UX for AI in Regulated Workflows

In banking and insurance, AI must fit the way people actually work. Generic chatbot patterns often fall short because users need explanations, evidence, approvals, and clear escalation paths before they can trust the output.

We redesign human-AI collaboration for regulated processes such as claims, underwriting, servicing, compliance, and case work. The result is a better interaction model, stronger trust calibration, and safer adoption of AI in day-to-day operations.

Platforms for AI at Scale

Successful AI programs need more than models. They need the engineering and control layer that makes AI repeatable, secure, observable, and easier to scale across teams and use cases.

We help clients build the platform foundations for agent and LLM operations, data governance, security, AI pen testing, and cloud deployment. We deliver for both public and sovereign cloud environments so institutions can scale with the right balance of performance, control, and regulatory fit.

Related Cases

LLM-Agnostic Agent Orchestration Platform Proven Internally at Enterprise Scale

Built in-house before taking it to clients, this secure-by-design, LLM-agnostic platform orchestrates work across custom systems, Atlassian and Microsoft tools for 2,000 employees.

Enterprise GenAI Platform and LLM Gateway for a European Universal Bank

For a European Universal Bank, we designed a GenAI platform with centralized LLM access, APIM-based logging, guardrails, private endpoints, and reusable Azure services

Outlining AI strategy for financinal services company

How We Take AI from Idea to Scale

Prioritize the Right Opportunity

We assess where AI can create real operational or customer value and where stronger controls are needed before scale.

At this stage, we support you through:

AI opportunity and workflow assessment
Value, risk, and readiness scoring
Operating model and governance review
Selection of the right first use case

Design & Build the Right Solution

We shape the human, technical, and governance model together so the solution is useful, trusted, and deployable.

At this stage, we support you through:

Workflow and interaction design
Prototype or MVP build
Control design and evaluation setup
Platform, integration, and security engineering

Scale with Confidence

Once the first use case works, we help clients scale through platform foundations, reusable practices, and team enablement.

At this stage, we support you through:

AI CoE setup and capability transfer
LLM/agent operations and monitoring
Data governance and security hardening
Roadmap for broader rollout and adoption

Technology Ecosystem Partnerships

NVIDIA

GCP

MS Azure

AWS Partner Advanced Tier Services

Databricks

UiPath

Snowflake

Datrics

Datuum

Relari

Our RTP Philosophy and Vision

Reliability

Focus on helping you achieve your business goals - both current and long-term
Battle-tested processes ensuring uninterrupted service & robust quality control
Rigid quality control with a range of KPIs to track delivery quality and efficiency

Transparency

Regular status updates & reporting at different management levels
Clear, predictable, and consistent billing with full expenditure reports
PM tools of your choice (Jira, Confluence, Azure DevOps) & clear project flow tracking

Partnership

Tailor-made solutions & focus on delivering value, not just performing the tasks
Finding new ideas & the most effective solutions for your individual case
Continuous optimization and enhancement of service delivery & performance

Frequently Asked Questions

We help clients identify high-value AI opportunities, redesign workflows, build governed AI capabilities, and create the platform foundation needed to scale across business functions. This covers strategy, UX, engineering, governance, security, and delivery.

Yes. A core part of our approach is turning promising pilots into usable, controlled, and production-ready capabilities with the right operating model, controls, and engineering foundations.

We embed governance into the service design from the beginning, including approval paths, auditability, oversight, evaluation, security, and documentation. For financial institutions, these controls are part of the product—not an afterthought.

We do both. We help clients frame the right opportunity and operating model, and we also design, prototype, engineer, and implement the solution with the controls needed for real-world use.

Yes. We support AI delivery across public and sovereign cloud environments, depending on the client’s regulatory, security, and operating requirements.

Our model is designed around transparency, delivery in the client environment, and capability transfer. In our AI CoE approach, clients retain ownership of assets and build the internal ability to run and scale the capability over time.

Our Offices

Bucharest, Romania

From AI Pilots to Governed Scale

What We Do

What You Get

Our Clients Choose Us For

Build your own AI capability

Improve workflows with agentic AI

Make AI usable in regulated work

Create the foundation to scale

Unlock AI Value

Redesigning Work for Measurable Value

AI CoE as a Service

AI Experience and Platform Foundations

UX for AI in Regulated Workflows

Platforms for AI at Scale

How We Take AI from Idea to Scale

Prioritize the Right Opportunity

Design & Build the Right Solution

Scale with Confidence

Related Services

AI Consulting Services

Modernization & Migration

AI Solutions

Financial Services Technology Consulting

Big Data Analytics Consulting

Regulatory Compliance Consulting

Technology Ecosystem Partnerships

Our RTP Philosophy and Vision

Reliability

Transparency

Partnership

Frequently Asked Questions

What kinds of AI services do you provide for banks and insurers?

Can you help us move from AI pilots to production?

How do you address governance and regulatory concerns?

Do you work only on strategy, or can you also build?

Can you support public and sovereign cloud environments?

How do you avoid creating dependency on external consultants?

Our Offices