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Execution-first AI agents for enterprise workflows, systems, and internal tools.

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June 6, 2025

Rierino

Portugal Agents

2,188

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Agents API MCP (Model Context Protocol)Local

Execution-first AI agents for enterprise workflows, systems, and internal tools.

Agent Agent Orchestration Agentic Workflows AI Agents API API GatewayFree + from $0.75

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Overview

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Rierino helps teams build and deploy tool-using AI agents that do real backend work—safely. Instead of chat-only assistants, Rierino agents can execute governed actions across workflows, integrations, and APIs, with structured logic and guardrails.

Use low-code orchestration flows, rules, visual queries, and reusable building blocks to create agentic workflows like approvals, onboarding, operational triage, data enrichment, and service processes. You can also embed agent actions into internal tools (e.g., CRM or ops screens) so users can trigger agent-assisted outcomes directly inside business workflows.

Rierino is designed for enterprise execution builders (developers, architects, platform/integration teams) and delivery teams (agencies/independent architects) who need to prototype quickly and move to production-grade deployment when requirements grow.

You can start with the Community Edition on AWS Marketplace here: https://aws.amazon.com/marketplace/pp/prodview-up2fcxku3k742

When you’re ready for production-grade requirements (scale, availability, governance, and support), Rierino also offers multiple paid deployment options.

Supported features

Key Features

Tool-using Ai Agents
Agentic Workflows
Low-code Execution Builder
Mcp Servers Tooling
Human-in-the-loop Approvals
Apis & Integrations For Actions

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Initial release

June 6, 2025

Initial release of Rierino.

Author

Berkin Ozmen

@berkinozmen

CTO @ Rierino

🇵🇹 Portugal

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Joined: June 2025

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Related topics

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Pros and Cons

Pros

Execution-first AI agents (agents that run real backend actions)

Tool-using agents with integrations and APIs

Agentic workflows with orchestration (flows/sagas)

Conditional flow logic for multi-step execution

Low-code backend automation with reusable building blocks

Visual queries and rules for governed decisions

Drag-and-drop UI builder for smart internal tools

Embed agent actions inside internal UIs and workflows

Composable APIs and microservices development

Rapid API and integration delivery for enterprise systems

Human-in-the-loop approvals for assisted execution

Language model integration (GenAI / LLMs)

MCP Servers tooling for exposing capabilities to agents

Strong fit for developers, architects, and platform teams

Useful for agency delivery teams building enterprise automations

View 10 more pros

Cons

Learning curve for teams new to orchestration and agentic execution

Best suited to technical builders (developers, architects, delivery teams)

Requires some setup and configuration to connect real systems/tools

Not intended for “instant app builder” use cases

Advanced production needs require paid deployment options

Q&A

What is Rierino?

wrote:

Rierino is an execution-first, low-code platform for building backend systems: workflows, integrations, composable APIs, and internal tools. It’s designed for teams that need structured orchestration and reusable building blocks, with optional AI agent capabilities for automating real operational work.

What makes Rierino “agentic”?

wrote:

Rierino supports tool-using AI agents that can trigger actions across workflows, services, and integrations. Instead of stopping at chat responses, agents can execute governed steps (e.g., call APIs, run queries, start flows, update records) while following rules and structured logic.

What is the AI Agent Builder in Rierino?

wrote:

The AI Agent Builder is where teams configure agents, model behavior, and connect agents to tools and execution capabilities. It enables agents to operate inside real backend processes—so you can embed AI assistance into workflows and applications, not just run standalone prompts.

What can I build with Rierino Community Edition?

wrote:

Rierino Community Edition (single-node AWS AMI) is the full Core platform for hands-on building and evaluation. Teams commonly use it to prototype tool-using agents, orchestrated workflows, integration flows, CRUD services, and internal tools—then move to production-grade deployments when they need higher availability, scale, governance, or support.

How does Rierino handle workflows and orchestration?

wrote:

Rierino uses flow-based orchestration (including saga-style patterns) to model multi-step backend execution. This makes it easier to implement conditional paths, retries/fallbacks, approvals, and structured handoffs across systems—without hard-coding every edge case.

How do “visual queries” and rules fit into agentic workflows?

wrote:

Visual queries and rules provide a structured layer for decisions and data logic. They can be used to validate inputs, route work, apply business rules, and create safe guardrails around agent actions—so AI execution remains predictable and auditable.

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Can Rierino build APIs and CRUD services?

wrote:

Yes. Rierino can expose composable APIs and services (including CRUD patterns and database-backed operations) and connect them to workflows and internal tools. This is useful for building reusable backend capabilities that power web apps, mobile apps, and operational automation.

How does Rierino integrate with external systems and APIs?

wrote:

Rierino is designed for integration-heavy environments. Teams can connect external systems (e.g., ERP, CRM, commerce, identity, data services) and orchestrate multi-step interactions across them using reusable services, flows, and controlled execution.

What is MCP support in Rierino?

wrote:

Rierino supports MCP Servers to expose tools and capabilities to AI agents. This helps teams standardize how agents access actions and resources, and keeps tool execution consistent across different agent use cases.

Who is Rierino best suited for?

wrote:

Rierino is best suited for enterprise execution builders (developers, architects, platform/integration teams), delivery builders (agencies and independent solution architects), and lean teams modernizing operational execution. It is most effective when the goal is orchestrated backend automation rather than purely UI-only app building.

How can Rierino be used in ecommerce or composable commerce?

wrote:

Rierino can orchestrate commerce operations across systems—catalog, pricing, orders, fulfillment, and customer service—by exposing composable APIs and connecting workflows across commerce engines, ERP/finance, CRM, and data services. Agent actions can assist with operational tasks like triage, exception handling, and content workflows.

How can Rierino help government or public sector workflows?

wrote:

Rierino supports structured workflows for onboarding, case handling, approvals, and secure system integration. Agent capabilities can assist with document-driven tasks (summaries, classification, routing) while keeping execution governed through rules, flows, and controlled integrations.

How can Rierino be used in banking or regulated operations?

wrote:

Rierino can orchestrate controlled operational workflows—requests, approvals, reconciliations, and service processes—across multiple systems with clear conditional logic. Agent actions can assist with routine operational steps while keeping execution structured and traceable.

What are examples of “smart internal tools” built with Rierino?

wrote:

Teams build internal operational screens such as CRM/contact management, approvals dashboards, onboarding checklists, service request queues, and admin tools. These UIs can include embedded agent actions—for example, drafting outreach messages, suggesting next steps, or summarizing records.

Which LLMs can Rierino work with?

wrote:

Rierino supports multiple LLM providers, including OpenAI, Anthropic, Azure OpenAI, Gemini, GitHub Models, HuggingFace, Mistral AI, as well as options for local and self-hosted models via LocalAI and Jlama.

How does LLM integration work in Rierino?

wrote:

LLMs are configured as GenAI models and used within agents and workflows. Rierino connects LLM calls to structured execution—tools, APIs, queries, and flows—so outputs can drive real actions under controlled logic (rules, validations, approvals, and conditional paths).

What makes Rierino different from “AI agent frameworks”?

wrote:

Many agent frameworks focus on building agent logic in code and running tool calls, but they often leave orchestration, governance, and operational execution patterns to the engineering team. Rierino is designed as an execution-first platform: agents can trigger workflows, call services, and follow governed paths using low-code orchestration, rules, and reusable building blocks.

What makes Rierino different from workflow automation tools?

wrote:

Workflow automation tools are often optimized for lightweight business automations and simple connectors. Rierino is built for backend execution: orchestration patterns, composable APIs, database-backed logic, and integration-heavy enterprise workflows—plus agent actions that operate inside those execution paths.

What makes Rierino different from traditional low-code app builders?

wrote:

Traditional low-code platforms often prioritize UI speed and citizen development, with limited backend control. Rierino is developer-first and execution-focused: it emphasizes orchestration, services/APIs, integrations, rules/queries, and governed automation—so teams can build reliable backend capabilities and connect them to internal tools.

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