Yopeso AI-BOS

Move from AI pilots to production-ready intelligent business systems.

Yopeso's AI-BOS (Business Operating System) combines agentic workflows, enterprise knowledge, data pipelines, governance, and observability into a modular framework for building reliable AI solutions around your business operations.

Explore use cases
Production AI requires a system
Connect

Bring approved business data, documents, tools, and workflows together.

Govern

Respect permissions, approvals, auditability, and enterprise policies.

Operate

Monitor quality, cost, performance, and user adoption over time.

Improve

Use evaluations and feedback loops to make workflows more reliable.

Robbert Visser, Chief Growth Officer at Yopeso

Live webinar · Wed 4 November 2026 · 11:00 CET

See AI-BOS in action.

Join Robbert Visser, Chief Growth Officer at Yopeso, for a free live session on turning the AI Act’s extension to December 2027 into a real operating model, before someone closes the gap for you.

45 minutes · Live Q&A · Free to attend

Register now →
Why AI-BOS

Enterprise AI needs more than a chatbot.

AI adoption is moving fast, but production AI systems introduce challenges that simple prototypes do not solve: fragmented data, permission boundaries, uncertain answer quality, slow workflows, and limited operational visibility.

Fragmented enterprise data

Business knowledge lives across documents, data platforms, internal tools, and workflows. AI systems need reliable access to the right approved sources.

Security and compliance

Every team, region, source, and workflow can have different rules. Governance must be part of the architecture, not added after launch.

Quality you can measure

Reliable AI requires evaluations, known references, feedback loops, and visibility into where answers and workflow decisions come from.

Workflow resilience

AI must survive slow steps, integration failures, hidden dependencies, and changing source data without breaking the business process.

Business-user adoption

Users need guided workflows and familiar interfaces, not fragile demos that require specialist support for every task.

Continuous adaptation

Models, data, policies, and expectations change. Production AI needs an operating model for improvement over time.

What it is

A modular operating system for enterprise AI solutions.

AI-BOS is Yopeso's reference architecture and delivery framework for building AI-powered business applications. It brings together the building blocks needed for production AI: workflow orchestration, enterprise knowledge access, data pipelines, governance, integrations, observability, and evaluation.

Agentic workflow orchestration

Coordinate multi-step business processes with tools, context, routing, and human review points.

Governed knowledge access

Connect approved sources while respecting permissions, policies, and sensitive-data boundaries.

Repeatable data pipelines

Ingest, process, enrich, refresh, and validate the information AI systems rely on.

Evaluation and observability

Track quality, latency, cost, usage, and correctness so teams can improve with confidence.

Core principles

Designed for enterprise realities.

AI-BOS gives teams a practical foundation for secure, adaptable, and measurable AI delivery across complex business environments.

Composable & interoperable

Build with modular layers and clear boundaries so models, tools, sources, and deployment targets can change as needs evolve.

Secure & governed intelligence

Embed authorization, data permissions, auditability, policy enforcement, human oversight, and guardrails from the start.

Observable & adaptive

Track performance, usage, cost, answer quality, and drift. Improve continuously through evaluations and feedback loops.

Use cases

From knowledge assistants to multi-step business workflows.

AI-BOS can be adapted to different industries and maturity levels, from focused knowledge retrieval to governed workflows that support analysis, review, and decision-making.

Knowledge

Enterprise knowledge assistant

Connect AI to enterprise knowledge sources with retrieval, permission-aware access, and guardrails for internal documentation, policies, research, and operations.

Analysis

Investment and domain analyst workflows

Support research and analysis workflows that combine structured data, documents, source validation, summarization, comparison, and decision support.

Documents

Document generation and review

Assist teams in creating structured business documents from approved templates and source materials while keeping review and quality controls in place.

Interfaces

AI gateway for existing workspaces

Expose AI capabilities through interfaces your teams already use while keeping orchestration, policies, and monitoring centralized.

Data

Data enrichment and knowledge pipelines

Use repeatable pipelines to extract, process, enrich, and refresh knowledge sources so AI applications stay current and reliable.

Quality

Evaluation and quality monitoring

Measure correctness, latency, cost, and behavior over time. Detect regressions and validate changes before they reach users.

Delivery lessons

Built from the issues real AI projects face in production.

The hard problems are rarely limited to choosing a model. They appear when AI systems need to connect to enterprise data, respect permissions, produce consistent answers, survive integration failures, and support business users who need reliable workflows rather than demos.

Source reliability

Align retrieval with the correct approved sources, folders, datasets, and document versions.

Permission-aware access

Ensure users only retrieve and act on information they are allowed to access.

Workflow resilience

Reduce failures caused by brittle routing, slow execution, integration timeouts, or hidden dependencies.

Answer-quality validation

Compare AI output against known references, expected answers, verified data, or human-reviewed examples.

User adoption

Package AI capabilities into guided workflows and familiar interfaces so business users can adopt them with less friction.

Architecture

The building blocks for production AI.

AI-BOS keeps the architecture modular, so every engagement can start with the client's actual workflows, data landscape, risk profile, and business goals.

Governance & security across every layer
Business channels
Web and mobile apps
Internal tools
Chat and agent workspaces
Identity & access
AI workflow orchestration
Workflow routing
Agentic task execution
Tools and human review
Knowledge & data fabric
Approved documents
Structured enterprise data
Context, memory, and sources
Data pipelines
Ingest and extract
Enrich and validate
Refresh and quality checks
Observability & evaluation foundation
Why Yopeso

AI strategy, architecture, and engineering delivery in one team.

Yopeso helps clients turn AI opportunities into working systems — from discovery and architecture to prototype, production, and continuous improvement.

Product thinking

Start from business value, user workflows, and adoption needs.

Engineering depth

Design maintainable systems that integrate with real enterprise environments.

Data and quality focus

Build the pipelines, evaluations, and feedback loops needed for reliable AI.

Governance-first delivery

Address permissions, traceability, and compliance before they become blockers.

Ready to turn AI ideas into governed business systems?

Talk to Yopeso about how AI-BOS can support your enterprise AI roadmap, from first use-case discovery to production-ready implementation.

we are global

Discover our locations around the globe

San Francisco | US

3739 Balboa Street, Unit #5049,
94121, San Francisco

Berlin | DE

Templiner Strasse 12,
10119, Berlin

Chisinau | MD

Str Bucuresti, nr 67
2012, Chisinau

Cluj-Napoca | RO

Strada Henri Barbusse 46,
400616, Cluj-Napoca

Kota Kinabalu | MY

F-31/32-5, KK Times Square
88100, Kota Kinabalu