Recenzo – AI-powered Google review management
Multi-tenant platform managing Google reviews across multiple business locations from a single dashboard
Production AI engineering for B2B software teams
AI features built for real-world use.
We build AI features and unblock pilots that need integration, evaluation, or cost controls. We start with the user problem and prepare the release inside your product, with clear technical ownership.
A clear first step
Agreed goal. Work directly with the founder. A result you can evaluate.
See where we enterProject outcomes and delivery experience
Our specialty
Production AI engineering.
From AI features to system integrations, we define what needs to change for users and how to evaluate the result.
Explore the offer- 01
Ship an AI feature
We build the feature, connect data and APIs, and integrate it into the user experience, in an existing or new product.
- 02
Harden an AI pilot
We investigate failures and edge cases, add evaluations, monitoring, and fallback paths, and set cost boundaries for rollout.
- 03
Unblock the foundation
We connect APIs, data, and systems and address application or cloud blockers. Integration can also be a standalone project, without AI.
From our projects
Selected work.
Business networking and collaboration platform
40+ person team coordinated over 1.5 years, from architecture to production
SwiftShop: Enhanced Customer Experience with AutoRAG
62% lower first response time for support interactions
Jobful – gamified recruitment platform
95% code reuse between Android and iOS, with native performance on both platforms
Definition of done
What we prepare for production use.
Alongside the model, we design the checks, boundaries, and tools needed by the people using and maintaining the system.
- 01 Repeatable evaluations and acceptance criteria
- 02 Data access, permissions, and auditability
- 03 Guardrails, fallback paths, and human intervention
- 04 Tracing, metrics, and operational alerts
- 05 Explicit cost and latency boundaries
- 06 Documentation, rollout, and ownership handover
Brainic method
Four stages. One technical owner.
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01
Goals & constraints
Clarify the problem, intended users, decision-maker, and project boundaries.
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02
Assessment & acceptance
Define architecture, risk, and what an acceptable outcome means.
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03
Build & evaluate
Ship vertical slices, integrate into the stack, and measure real behavior.
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04
Launch & handover
Prepare the rollout, monitoring, and documentation for technical handover.
Founder-led delivery
From the first conversation to technical decisions: Silviu.
Silviu Stroe leads assessment, architecture, and delivery. We agree what Brainic owns and how we work with your team, adding specialists when the project calls for them.
We use AI development tools with human review of the implementation. People remain accountable for decisions and delivery.
How the studio operatesFit
Start with the problem, not the project label.
What we clarify together
- The problem and who would benefit from solving it
- The person who sets priorities and accepts the result
- Data, systems, and access needed for the proposed phase
- A first step that fits your budget and priorities
We can also discuss
- MVPs and new products with a specific problem to validate
- Web or mobile apps, websites, and integrations, with or without AI
- Working with your team on implementation or additional engineering capacity
- Technical assessment and architecture, including before choosing who will implement
You do not need a complete brief or an in-house technical team to get in touch. We clarify what we can take on, what needs preparation, and whether an existing solution would be enough.
First step
What would you like to build or improve?
Tell us what you want to achieve and where you need help. We clarify the first step together, whether the project involves AI or not.