Agentic AI engineering — from Romania
Most teams have run an AI pilot. Few have agents doing real work. We design, build and run AI agents, and everything they stand on, so yours make it all the way to production.
01 — Services
Agents need more than a model. They need integrations, clean data, evaluation and a solid platform. We deliver the whole drivetrain with one senior team.
Agents that do real work inside your business, not just answer questions.
We design and build autonomous and human-supervised agents for the workflows that slow you down: document handling, customer and back-office operations, knowledge work, and net-new AI features inside the products your users already rely on.
Put AI agents to work across your engineering lifecycle.
We roll out coding agents such as Claude Code across your teams and redesign how software gets specified, built, tested and reviewed, with quality gates in CI/CD so humans keep ownership of every decision, merge and release.
The architecture that lets agents reach your systems safely.
Reference architectures, orchestration patterns and Model Context Protocol servers that connect models to your internal tools, APIs and data, built on Amazon Bedrock, AgentCore and the cloud you already run.
Agents are only as good as the data they stand on.
We build the pipelines, connectors and retrieval layers that ground agents in your governed data, with retrieval-augmented answers that cite their sources and respect who is allowed to see what.
Know what your agents do, what it costs, and when it drifts.
Evaluation suites before launch, monitoring and tracing after it, and cost guardrails throughout, so agent behaviour stays explainable and every release is measurably better than the last.
Everything an agent needs around it to run in production.
Secure, cost-efficient cloud platforms with infrastructure as code, plus the web, mobile and backend software the agents live inside, delivered by the same senior team.
02 — How we engage
Pick the entry point that fits where you are. The first use case proves the pattern, and every one after it moves faster.
Find the right first agent
Workshops with your business and engineering leads to map candidate use cases, rank them by value and feasibility, and agree on clear success criteria.
Working software, not slideware
A tightly scoped agent or integration built against your real use case and data, so you judge results before you commit to a full build.
Milestones you can measure
From validated prototype to a production-grade deployment with integrations, guardrails and evals, delivered against agreed milestones.
Embedded in your team
Senior AI engineers and leads join your sprints and channels for a fixed term, build alongside your people, and hand over the running agents, tooling and runbooks.
Agents keep getting better
Ongoing operation of your agents: monitoring, evaluation, cost tuning and iterative improvements driven by how they are actually used.
03 — Process
We build with an agentic delivery loop. AI agents handle requirements, drafts, tests and reviews, while senior engineers set direction, resolve trade-offs and approve every release.
Shift 01
Agents interview stakeholders and draft specs and acceptance criteria. You confirm what success means.
Shift 02
Architecture, UX and key technical decisions are drafted and recorded. Senior engineers sign off.
Shift 03
Agents plan, implement and test in small, reviewable steps. Engineers steer and step in on risk.
Shift 04
Code, experience and AI behaviour are reviewed against the spec. Humans are the final approvers.
Shift 05
We deploy, measure real usage and feed what we learn into the next iteration.
04 — Security & responsible AI
An agent that can act inside your systems needs the same discipline as any engineer with production access. Every engagement ships with security, governance and oversight designed in from the first sprint.
Single sign-on, scoped identities and least-privilege permissions for every agent and tool.
Credentials kept in managed secret stores, never in prompts, code or logs.
Designed around GDPR and data residency requirements, with clear boundaries on what agents can read.
Guardrails, human approval for sensitive actions, evaluation before deployment and audit trails.
05 — Why GearShift
We are a senior engineering team from one of Europe's strongest tech hubs. We pair hands-on product and cloud engineering with deep work on Claude, Amazon Bedrock and the Model Context Protocol.
We don't sell decks. We put working agents in front of your team, measure them, and leave you owning the code, the platform and the know-how.
Success is an agent your people use every day, not a demo that impressed once.
Agents move fast. People set direction, approve the risky steps and own every release.
Code, agents, runbooks and skills transfer to your team. No black boxes.
Ready when you are
Tell us which workflow you want an agent to take on. We'll come back with a plan for the first gear.