Tool silos
Single AI tools do not create reliable end-to-end workflows.
AI Agent Orchestration
Construye AI workflows gobernados para trabajo operativo de alto volumen
Mapeamos, prototipamos y operacionalizamos AI agent workflows que conectan tools, datos, QA checks y aprobaciones humanas para automatizar trabajo repetitivo sin perder control.
Experiencia del founder conectada con equipos y marcas comotrivagoCoIQinneOviva
InputBrief, data, files
Research AgentCollects and analyzes information
Analysis AgentStructures and evaluates
Drafting AgentCreates drafts and outputs
QA AgentChecks quality
Human ApprovalReview and release
ExecutionPublishing and automation
Why AI pilots fail to become business workflows
Most teams can test AI tools. The hard part is turning them into reliable, reviewable workflows that survive real data, edge cases and team handoffs.
Context breaks
Inputs, decisions and files are passed inconsistently between steps.
No QA layer
Outputs are used before quality, policy or brand checks happen.
No approval gate
Teams do not know where human judgment belongs.
No logs
When something fails, nobody can inspect what happened.
Control model
A practical operating layer for agent workflows: what agents may read, what they may do, when they must ask and how every decision can be reviewed.
Source systems
Define which CRMs, documents, dashboards, inboxes or databases the workflow can read.
APIs and tools
Specify the actions agents may trigger and which systems require human confirmation.
Agent roles
Split research, drafting, checking and execution into clear responsibilities.
QA checks
Add quality, consistency, factual and policy checks before release.
Approval gate
Route important outputs to a named human owner before publishing or sending.
Logs and override
Record inputs, outputs, decisions and exceptions so a person can pause, correct or reroute the workflow.
Choose the right starting point
What you leave with
Discovery Sprint
Map processes, evaluate opportunities and define prioritized workflows.
Reservar Agent Workflow Audit →Prototype Build
Design, test and validate one controlled workflow.
Reservar Agent Workflow Audit →Agent Operating System
Scale governance, enable teams and improve the system over real usage.
Reservar Agent Workflow Audit →What you leave with
Opportunity map
Prioritized workflows based on frequency, risk, data access and expected leverage.
Workflow blueprint
Roles, handoffs, states, approval points and exception paths.
Integration spec
Required tools, APIs, permissions and data sources.
Prompt and guardrail library
Reusable instructions, examples, checks and escalation rules.
Pilot workflow
A working first version tested on real tasks with human review.
Operating playbook
Documentation for owners, cadence, QA and continuous improvement.
Where agent workflows usually pay off first
CRM enrichment agent
Researches accounts, prepares CRM updates and routes proposed changes to sales or RevOps before anything is written back.
Slack approval workflow
Sends drafts, exceptions and decisions to the right owner before execution.
Knowledge agent for Notion or Drive
Finds, structures and cites company knowledge for repeated tasks.
Reporting QA agent
Checks recurring reports for anomalies, missing context and decision risks before leadership sees the summary.
n8n or Make automation pilot
Turns a repeated process into a tested workflow with human gates.
Content repurposing workflow
Converts approved assets into channel-specific drafts with QA and approval.
Encuentra el primer workflow que vale la pena automatizar
En un audit identificamos proceso, sistemas, puntos de aprobación y riesgos, y definimos el piloto controlado más rápido de construir.