Services
AI Engineering
AI built into the platforms, operating model and products you already run.
Explore AI EngineeringCloud Development
Scalable, secure cloud solutions on AWS, Google Cloud and Azure.
Explore Cloud DevelopmentDevOps as a Service
CI/CD pipelines, infrastructure automation and reliability engineering.
Explore DevOps as a ServiceTransformation
Process automation, system integration and change management, to drive growth and efficiency.
Explore TransformationBig Data & Analytics
Data pipelines, warehousing and business intelligence.
Explore Big Data & AnalyticsMobile Development
iOS and Android apps, built with React Native and Flutter.
Explore Mobile DevelopmentUX/UI Design
Research-driven design that delights users and drives business results.
Explore UX/UI DesignTwo decades of engineering experience, reborn as an AI-native company. We build the layer where human judgment meets machine execution — so the software and processes you already run become capabilities that improve on their own.
Not a slogan — a practical change in how systems are built and run. The distance between a working demo and something a company can depend on is engineering.
Software used to be screens over a database, waiting for a click. Applications now hold context, make decisions and call other systems on their own.
A process used to be human steps supported by tools. Agents execute those steps directly, so the work moves to the boundaries, permissions and checks around them.
Models are the easy part to obtain. The layer around them — data access, integration, evaluation and day-two operations — is built by engineers, not bought.
Every organization already runs on people, processes, systems and data. What is new is the layer between them — and it needs an engineering partner to build it, integrate it and keep it running.
How we engineerAgents take on a growing share of the operational work. That is capacity, not authority — decisions that carry consequence stay with senior people. We build the span between the two, and we stand on it.
Boundaries, data models, and the decisions expensive to reverse.
What agents may touch, what requires approval, where the audit trail must hold.
Threat model, access, secrets, compliance posture — reviewed every engagement.
The standard the work is measured against, and whether it is met.
Trade-offs, escalations, and anything touching your customers, money, or risk.
Writing code against an approved specification, inside agreed boundaries.
Unit, integration, and regression suites. Reproducing defects before a fix.
Watching services, surfacing anomalies, drafting the first incident report.
Dependency upgrades, migrations, scheduled jobs, and the maintenance backlog.
Keeping references, runbooks, and change logs current with the system.
Extraction, transformation, reconciliation, and reporting at volumes beyond hand work.
Not a pipeline, not a policy — a person, on the record, answerable for what shipped.
Autonomy is not a department. It is a property a process earns once its inputs, rules and outcomes can be engineered — after which people supervise the work rather than perform it.
Requests are triaged, answered and resolved on arrival — only judgment calls reach a person.
Research, qualification and follow-up run continuously, not in bursts between meetings.
Invoicing, reconciliation and reporting run themselves; exceptions are raised for review.
Onboarding, approvals and handoffs move on their own instead of being chased.
Scattered documents become one system that answers in context, with sources cited.
Migrations, refactors and maintenance run on agents under senior review.
Your data arrives as a briefing with a recommendation, not as another dashboard.
Intent becomes specification, code and tests on a production line with a human gate.
Contracts, forms and statements are read, extracted and routed as they land.
Controls are checked continuously; evidence is collected as work happens.
Forecasts, schedules and capacity models update themselves as conditions change.
This list is not the boundary. Anything well understood can be specified — and anything specified can become increasingly autonomous.
AI engineering, agentic automation, software engineering, deep business integration and strategic consulting are a unified architecture — built to be installed, not assembled on site.
The same foundation carries a five-person startup and a multinational. What changes is depth, not architecture.
Four layers. Every instruction, exception and handoff passes through people first.
One layer inserted. People set intent and hold judgment; agents carry the work down the stack.
We do not merely automate tasks. We engineer the foundation underneath that layer — so every process handed over makes the organization measurably more autonomous.
Models, prompts, evaluation and inference infrastructure, versioned like production software.
Defined roles, tools and boundaries — testable components, not scripts held together by hope.
Documents, records and institutional context, structured so agents can reason over them.
Agents wired into the systems you already run: ERP, CRM, ticketing, finance, the internal tools nobody documented.
Multi-step work coordinated across agents, services and people. State survives failure and restart.
Least-privilege access, isolated execution, and a record of every action an agent takes.
Explicit policy on what an agent decides alone, and where a human signs off.
Every run traced, measured and costed. Production behaviour is observed, not assumed.
Production signals feed back into evaluation sets. The system gets better with use.
Agents raise the value of engineering — they do not remove the need for it. An AI-native business is still a software business, and that software has to hold under load, under attack, and under change.
A model on its own knows nothing about your company. Value appears when agents connect to what already exists — your systems, your rules, and the people who sign off on decisions.
Not demos. Not a chatbot bolted onto a website. What we ship runs inside your operating environment — versioned, tested, permissioned, observed, and accountable to a named owner. It handles real volume and real edge cases.
Models are probabilistic. Production is not. What makes an agent safe in front of a customer is not the model — it is the tests, boundaries, observability, rollback path, and review gate around it.
“If it cannot survive Monday morning,
it does not leave the studio.”
Twenty years and 100+ projects of shipping and operating production systems — through incidents, audits, and migrations — is what we bring to the AI layer. We build agents the way we have always built systems: observed, constrained, and answerable.
AI EngineeringThe architecture stays the same from one industry to the next. What changes is the knowledge that goes into it: the systems a sector runs on, its rules, and where its judgment calls sit.
Selling to people, and bringing them back. The largest body of work in the portfolio.
Products people open every day, where attention is the constraint and slowness is the failure.
The systems a company runs on and the goods it moves. The buyer owns operations or IT, not a product.
Systems of record for value, where every balance has to reconcile and every figure has a lineage.
A category created by legislation, so the demand is not discretionary and the numbers have to survive an audit.
A stage rather than a sector, backed by the seven ventures East Wolf has built as operator rather than supplier.
Not on the list? The foundation does not change with the industry. Bring us the process, and we will tell you how we would build it.
Book a callOur AI-native software production platform. It changes how software is specified, built, tested and delivered — agents doing the work, engineering governance holding the line.
Where we are heading: you pay per usage or per outcome, instead of time and materials, fixed cost or long procurement. That could make projects a lot cheaper, with a better return on what you spend.
The Factory powers our own delivery. Every project we ship runs through it.
It becomes available as a standalone product, governance included.
Organizations build software themselves, on the same operating model, and pay per usage or per outcome.
Early access opens to a small batch of teams at a time, each with a senior engineer alongside.
Explore the FactoryModels are the easy part. Architecture, test coverage, integration with the systems a business already runs on, and the discipline to keep it in production — that is the work.
A software studio, started by engineers who had already spent years shipping production systems. The team’s experience goes back two decades.
We run East Wolf the way we build for clients: agents carry the work, and senior people set intent, hold judgment and sign what ships. Delivery works this way today. The rest of the company is following.
Models will be replaced many times over. The partner you depend on should not be. Fourteen rings so far, and we are building to add ten thousand more.
The core team stays small and senior. The network scales around it when depth is needed — never instead of it. Bucharest, shipping to production for organizations of every size.
See our workA process worth automating, a system worth modernizing, or just a question about where agents fit. Tell us what you need and we will tell you how we would build it, how long it takes, and what it costs.
A confirmation email within 12 hours.
A call with our team to discuss.
A Lead and FDE are assigned.
Success metrics defined.
A Forward-Deployed Engineer is a senior engineer embedded with your team to ship quickly. It is our standard approach; the team and process are tailored to your goals.