AgenticAI Solutions
From individual tasks to autonomous departments and companies. Sunesis builds digital agent teams that independently execute connected business processes, from the initial request to the final outcome. Where the nature of the business allows, they can run company-wide operations within defined rules and permissions; people step in for exceptions and matters requiring their judgment, attention or approval.
Sunesis designs and builds enterprise-grade AgenticAI solutions that go beyond conversation — helping organizations automate complete workflows, support employees and customers, connect enterprise knowledge with business systems and operate AI safely in production.
Our AgenticAI solutions combine AI agents, enterprise AI assistants, digital agent teams, RAG, tool use, APIs, Business APIs, deterministic workflows, human approvals, auditability and production-grade governance.
Most projects are accelerated by KumuluzAI, our governed AgenticAI platform for secure, integrated and production-ready AI agents, assistants and agentic process automation.
Built for organizations that need secure, integrated and governed AI — not another isolated chatbot.
Many organizations start their AI journey with chatbots, document search or isolated assistants. These can be useful, but they often become disconnected initiatives — each with its own model, prompts, knowledge base, integrations, permissions, monitoring, cost structure and compliance risks.
Sunesis helps enterprises take the next step: building AgenticAI solutions that are integrated into real business processes and managed through a common, secure and governed foundation.
We design AI agents and assistants that can understand context, access approved enterprise knowledge, use tools, call APIs, work with Business APIs, participate in workflows, involve humans when needed and support multi-step business processes — with governance, traceability and control built in from the start.
For selected operational areas, we can also help organizations move toward agentic operating models, where specialized AI agents handle much of the routine, knowledge-intensive and coordination-heavy work, while people supervise, approve sensitive actions, handle exceptions and remain accountable for outcomes.
AgenticAI is not only about answering questions. It is about connecting AI reasoning with enterprise knowledge, tools, APIs, workflows and business execution — under governance.
A chatbot answers questions. An enterprise AgenticAI solution helps get work done. AgenticAI systems can reason about a task, plan steps, retrieve relevant knowledge, use approved tools, interact with enterprise systems and support the execution of business processes.
In enterprise environments, this requires much more than access to a language model. It requires identity, authorization, auditability, security guardrails, integration architecture, cost control, model governance, human oversight, deterministic execution boundaries and reliable operations.
This is where Sunesis brings together AI engineering, enterprise software development, cloud-native architecture, API integration, DevOps and our own KumuluzAI platform.
AI agents are not just for helping employees with individual tasks. Sunesis also builds solutions where coordinated digital agent teams take on the full operational work of a department or, where the nature of the business allows, a company.
Agents receive requests, plan and allocate work, gather information, carry out activities in business systems and coordinate processes across business functions. Within agreed rules, permissions and risk limits, they execute the process without ongoing human intervention.
They hand over only matters that exceed these boundaries or require a human decision or mandatory approval. Each handover includes context, the reason for escalation and proposed next steps. People retain responsibility for setting goals, oversight and final accountability.
Agents do the work. People set the direction and decide where human judgment is needed.
Multiple specialized agents collaborate across a process, each responsible for a defined role such as intake, classification, validation, knowledge retrieval, decision support, approval preparation or execution support.
We automate complete workflows where agents coordinate tasks, use business systems, prepare outputs and trigger deterministic workflow steps.
Digital agent teams can take on the full operational work of a department and coordinate it across business functions, within defined rules and under human oversight.
People remain in control where judgment, accountability, risk, customer relationship or regulatory requirements demand human involvement.
Agents execute complete processes, from the initial request to the final outcome, without ongoing human intervention within agreed permissions and risk limits.
Agents hand over cases that exceed their permissions or require human judgment or mandatory approval, including context, the reason for escalation and proposed next steps.
Autonomous execution requires more than technical monitoring. Just as a manager oversees a team, oversight mechanisms need to check whether agents perform the right activities, follow business processes and deliver the expected outcomes.
Check the substantive quality of results, adherence to business rules, required approvals and the correct flow of activities — not just whether the system is running.
Identify skipped steps, inconsistent decisions, repeated failed activities, bottlenecks and unusual business outcomes.
Depending on the type and severity of a deviation, the solution triggers an authorized corrective action, pauses execution or hands the case to the responsible person with an explanation.
Continuous improvement of AI agents and business processes
Automation is not the end goal. When AI agents participate in business processes or execute them end to end, data from their work becomes the foundation for systematically improving efficiency, quality and operating costs.
We build solutions that use execution data to identify bottlenecks, unnecessary steps, recurring exceptions and opportunities to allocate work more effectively. They can improve how individual agents work, how agents collaborate and how the entire process runs — including processes involving people.
Improvements are validated against agreed business metrics and applied automatically within authorized boundaries. Changes to business rules, permissions or other important constraints remain subject to approval by the responsible people.
We do not just optimize AI agents. We improve how the entire business process works. The benefits below are goals whose achievement we measure, not guaranteed outcomes.
Less waiting, fewer unnecessary handovers and less rework.
Fewer errors and recurring exceptions, with more consistent results.
Better work allocation and lower resource consumption per completed case.
We build AgenticAI solutions for organizations that want to automate knowledge-intensive, document-heavy and process-driven work — without losing control over security, compliance or enterprise architecture.
Agents that gather context, retrieve knowledge, validate outputs and trigger approved actions across multi-step workflows.
Examples
Assistants for customers, employees and portals — with a path to grow into broader AgenticAI platforms.
Examples
Specialized agents that collaborate, share context and play distinct roles within a controlled process — moving beyond one-off assistants toward reusable process automation patterns and digital agent teams.
Example agent roles
We connect agents to approved documents, policies, knowledge bases and enterprise data so they act on controlled internal knowledge.
Key capabilities
Agents call approved capabilities through controlled interfaces rather than backend systems directly, with MCP integration where it fits.
Integration areas
We expose repeated business capabilities as reusable Business APIs — a governed layer between agents and enterprise systems.
Example Business API tools
Agents prepare context and recommend next steps, while engines like Temporal or Camunda execute process-critical steps under control.
Typical workflow patterns
For high-risk actions, users review, confirm or reject what an agent proposes before anything is executed.
Examples
Logs, decision traces and access policies showing what happened, who triggered it and which tools were used — supporting DORA, the EU AI Act and GDPR.
Governance areas
We move organizations from prototypes to production: deployment, security, monitoring, cost control, model routing and lifecycle management.
Architecture concerns
Organizations do not need to become AI-native overnight. Most start with a focused assistant or process use case and gradually evolve — from AI assistants to tool-using agents, workflow-connected agents, digital agent teams and AI-native operating models.
AI assists users by answering questions, explaining procedures and helping them find information. Outcome: better self-service, faster knowledge access and reduced support workload.
AI agents use approved tools and APIs to retrieve data, check statuses or perform simple actions. Outcome: more useful assistants that can interact with enterprise systems under control.
Agents participate in business workflows where critical steps are executed through deterministic workflow engines and Business APIs. Outcome: AI supports real process execution while maintaining reliability, auditability and human approvals.
Multiple specialized agents collaborate across an end-to-end process, each with a defined role and scope. Outcome: complex workflows can be coordinated by digital agent teams instead of a single assistant.
Selected operational functions or departments are redesigned around AI agents, Business APIs, workflows, governance and human supervision. Outcome: routine work is handled primarily by agents, while people focus on oversight, exceptions, expert judgment and accountability.
Most enterprise AgenticAI projects need more than a custom-built agent. They need a common platform so agents, assistants and AI applications are developed, managed and controlled consistently across the organization.
KumuluzAI provides the foundation for agent runtime, orchestration, enterprise knowledge access, tool integration, identity propagation, safety guardrails, model routing, auditability, cost control and centralized management — helping organizations avoid fragmented AI silos.
Single foundation
Agents, assistants and AI applications run on a common platform instead of each team building its own isolated stack.
Deployment
KumuluzAI can be deployed in the customer environment, supporting data residency, isolation and enterprise control.
Model routing
Sensitive data can stay within the perimeter, while less sensitive workloads use external providers through a controlled gateway.
Neutral
The platform abstracts model providers, helping organizations avoid lock-in and maintain an exit strategy.
Governance
Policies, identity, authorization, audit trails, human approvals and safety controls are part of the platform, not an afterthought.
Management
Agents, tools, knowledge sources, policies, prompts, costs, audit trails and approvals are managed from one place.
Without a platform strategy, AI initiatives quickly fragment. One department builds a chatbot. Another connects a model to internal documents. A third introduces an assistant through an external vendor. Each has its own knowledge base, permissions, monitoring, model provider, cost structure and compliance story.
A platform approach changes this. AI agents can be developed by different teams or partners, but they run on the same foundation, follow the same governance rules, use shared platform services and remain visible to the organization.
| Area | Isolated AI initiatives | Platform-based AgenticAI |
|---|---|---|
| Governance | Different for every solution | Unified across all agents |
| Identity & access | Implemented separately | Propagated across the full agent flow |
| Knowledge | Duplicated and inconsistent | Shared, controlled and traceable |
| Tools & APIs | Rebuilt per use case | Reusable governed tools and APIs |
| Costs | Hard to attribute and control | Centrally monitored and budgeted |
| Compliance | Proven separately each time | Built into the platform |
| Workflows | Often disconnected | Integrated with deterministic execution |
| Scalability | Grows into complexity | Designed for enterprise reuse |
AgenticAI introduces new risks because agents can use tools, call systems and execute actions. Sunesis designs clear boundaries — what an agent can read, what it can do, when it needs approval and how every action is recorded — into the architecture from the beginning.
Every agent action runs in the context of a known user, role or system identity, enabling consistent access control across agents, tools, knowledge and backends.
Agents retrieve information only from approved sources and according to the user’s role, context and access rights.
Agents can only use the tools and actions they are explicitly allowed to use, based on policies and the context of the task.
Actions that change data or trigger business effects can require additional approval and short-lived authorization before execution.
High-risk or sensitive actions can be routed to human reviewers, with clear context and traceability.
The solution can detect unsafe prompts, protect sensitive data, validate outputs and reduce the risk of misuse or unintended behavior.
Agent requests can be routed through API management layers where authentication, policy enforcement, monitoring and logging are applied.
Agent decisions, knowledge retrieval, tool calls, model interactions and approvals can be traced and reconstructed for operational, security and compliance purposes.
AgenticAI is especially useful where work depends on complex processes, distributed knowledge, documents, approvals and multiple enterprise systems.
Claims handling, policy workflows, customer requests, knowledge retrieval and document-heavy insurance processes.
KYC, customer onboarding, compliance checks, advisory processes and knowledge-intensive banking operations.
Helping employees find answers, understand procedures, prepare documents and access approved organizational knowledge.
Reducing manual work in repetitive administrative, operational and support processes across documents, systems and people.
AI agents embedded into web, mobile and other channels to guide users, collect information and execute process steps.
Agents prepare context, classify requests, summarize documents or recommend actions, while workflow engines execute business-critical steps deterministically.
KumuluzAI as a common foundation for multiple assistants, agents and applications across departments under central control.
AI agents handle much of the routine work, coordination and decision preparation, while people supervise, approve sensitive steps, handle exceptions and remain accountable for outcomes.
A production AgenticAI solution separates AI reasoning, knowledge retrieval, tool use, workflow execution and backend operations into clear layers — a safer and more maintainable architecture than connecting agents directly to backend systems.
Web applications, customer and employee portals, mobile apps, intranets, service desks and internal business applications.
AI agents, assistants, prompts, policies, model routing, knowledge retrieval, guardrails, human approvals and auditability.
Approved documents, policies, procedures, knowledge bases, intranet content, structured data and source-aware retrieval.
Agent-callable APIs, MCP-oriented tools, Business APIs, connectors and approved system actions.
API catalog, gateway, access control, routing, monitoring and policy enforcement through platforms such as Kumuluz API.
Temporal, Camunda or similar platforms for deterministic process execution, approvals, retries and long-running workflows.
CRM, ERP, core banking, insurance, document and case-management systems, databases and external services.
Audit trails, session logs, tool call records, usage analytics, model cost visibility and compliance reporting, together with business-level oversight, process conformance checks, anomaly detection and business outcome measurement.
We help organizations move from business opportunity to production-ready AgenticAI through a structured, pragmatic and engineering-driven approach.
We work with business and technology stakeholders to find processes where AgenticAI can create measurable value.
We define how agents are managed, which knowledge and systems they can access, which tools are approved and how approvals, auditability and compliance work.
We model agents, tools, prompts, knowledge retrieval, decision points, human approvals and deterministic workflow boundaries.
We develop a controlled MVP that validates value, feasibility, governance and user experience before scaling.
We connect the solution with internal APIs, identity providers, document repositories, data sources and workflow systems.
We implement audit trails, access policies, safety guardrails, human approval mechanisms, monitoring and cost visibility.
We support deployment, DevOps and production monitoring, measure business outcomes and enable controlled, automatic optimization of agents and complete processes against agreed metrics and approval boundaries.
After the first use cases prove value, more agents, knowledge sources, tools, APIs and workflows are added to the same foundation.
For selected areas, we help organizations redesign operating models around digital agent teams, Business APIs, workflows, governance and human supervision.
AgenticAI requires more than prompt engineering. It needs robust software architecture, secure integration, reliable orchestration, identity management, observability, DevOps and operational discipline.
Sunesis combines AI engineering with strong expertise in backend systems, APIs, event-driven architectures, cloud-native platforms, Kubernetes and DevOps.
We understand complex business environments, legacy systems, integrations, security requirements and operational constraints.
We pair AI engineering with backend and frontend development, integrations, cloud-native architecture and DevOps.
KumuluzAI is a reusable AgenticAI platform that accelerates delivery and avoids fragmented AI initiatives.
Identity, authorization, auditability, human oversight, data control and policy-based execution from the beginning.
Through APIs, Business APIs, connectors and workflows, agents support actual business operations — not only answers.
AI assists, reasons and prepares context, while deterministic engines execute business-critical steps.
We can help organizations move beyond individual assistants toward digital agent teams and agentic operating models for selected operational areas.
Banking, insurance, energy, public sector and enterprise environments where reliability and traceability matter.
We are already applying AgenticAI concepts in enterprise environments, helping organizations move from experimentation to practical business value.
An AgenticAI solution supporting intelligent assistance, knowledge-driven automation and business process optimization, combining enterprise knowledge, AI assistants and controlled integrations.
An enterprise AgenticAI platform enabling intelligent process automation, secure use of organizational knowledge and integration with business systems through governed knowledge access, tool use and API integrations.
A multimodal AgenticAI solution based on KumuluzAI, developed with UM FERI for SURS, that turns questions in Slovenian or English into traceable statistical and geospatial analyses. It connects data sources and presents results through interactive maps, charts and tables.
AgenticAI solutions often combine multiple Kumuluz products depending on the use case, integration needs and governance model.
Core platform for agents, assistants, RAG, tool use, model routing, approvals, auditability and governance.
API management and gateway platform for exposing, securing, monitoring and governing APIs used by applications, partners and AI agents.
Reusable business capabilities that can be used by AI agents, digital products and deterministic workflows.
Engineering foundation for building services, APIs, connectors, MCP-enabled tools and workflow-ready integrations.
If your organization is exploring how AI agents can automate workflows, connect to business systems and improve operational efficiency, Sunesis can help you design, build and operate a secure, governed and production-ready solution.
Start with one focused use case and evolve toward a reusable AgenticAI platform foundation — or toward broader agentic operations where digital agent teams support complete business processes.