How do you design a secure architecture for Applied AI?
A map of the execution points, contracts, and checks needed for an operation with a defined scope.
Guide for CTOResources
Understand. Prepare. Put into practice.
Guides, articles, case studies and experiences to choose the next step for your AI operation.
Architecture, security and operations
Prepare the decision around your context
What a CISO asks before putting Applied AI into production
A matrix of controls, enforcement points, evidence, owners, and outstanding items to decide on release.
Guide for CISOHow to track results and exceptions in an operation with Applied AI
An agreement on completion, metrics, and exception handling to guide day-to-day work.
Guide for COOFind material for this stage
43 resources found
Product and delivery
Forward Deployed Engineering for AI operations
See how Starya and your team investigate an operation, deploy improvements and verify outcomes. Explore the FDE approach through concrete examples.
Reference materialProduct and delivery
NebulaOS: the technology behind your operation
NebulaOS connects models, sources and tools and helps monitor the points included in the deployment.
Reference materialProduct and delivery
NebulaWorks: conversations, decisions and workflows
NebulaWorks is Starya’s work surface on NebulaOS: team conversations, decisions and workflows. Not the US consultancy of the same name.
Reference materialProduct and delivery
SaaS, dedicated infrastructure and data sovereignty
Compare SaaS and assisted deployment, explore data flows and understand the reference architecture for federated AI.
Reference materialProduct and delivery
Enterprise and Custom: how to buy
Explore Enterprise, Starya’s business offering, and Custom for tailored requirements. Define scope, deployment model and terms in a proposal.
Reference materialProduct and delivery
Trust Center: security, privacy and deployment
Access public documents and prepare to assess your deployment’s data, responsibilities and evidence.
Reference materialProduct and delivery
Differentiators and scale in AI operations
Explore the mechanisms connecting Starya’s technology and operational experience, with customer stories, sources and figures presented in context.
Reference materialGuide
How to choose an operation to start with
A guide to defining the process, the expected outcome, and who takes part.
Reference materialGuide
What to ask about AI already in use
Actions, access, and evidence to bring to the discussion with the team.
Reference materialGuide
How to organize operational monitoring
A routine for learning from failures, handoffs, and outcomes.
Reference materialGuide
How to hand a conversation over to the team
Prepare the context that allows a person to take over and continue.
Reference materialGuide
How to prepare a communication with AI
Organize the audience, content, timing, and continuity before sending.
Reference materialGuide
How to prepare for a deployment decision
Bring the environment, processing, access, and responsibilities into the same discussion.
Reference materialArticle
Your AI answered “done”. But was the task completed?
“Done” in the chat does not prove completion. The difference between the agent's response, the execution of the action, and confirmation in the target system, with an owner and evidence.
PublishedArticle
The work begins when the Applied AI operation goes into production
What to monitor after deployment: failures, handoffs, quality, and the operation's evolution.
PublishedArticle
How to choose the first operation for applying AI
Process, expected outcome, data, owner, and boundaries before choosing a solution.
PublishedCase
The operation showed where AI could help more.
From engagement in care pathways to appointment scheduling.
Summary of a published accountCase
Voice support with continuity for the team.
Authorization status checks and duplicate payment slips, with context passed along.
Summary of a published accountCase
From information gathering to quoting, with the salesperson kept in context.
Qualification and quoting through WhatsApp, connected to HubSpot.
Summary of a published accountCase
A report prepared by AI. An approval that remains human.
Organizing information for editable surgical reports.
Summary of a published accountCase
Welcoming support and referrals connected to the care team.
Support through WhatsApp during maternal health journeys.
Summary of a published accountCase
From each company's need to an operating solution.
Discovery, deployment, and ongoing support of agents for enterprise clients.
Summary of a published accountCase
The conversation needs to be connected to the operation.
WhatsApp communication integrated with agents and the human team.
Summary of a published accountLearning path
Start an operation
From the chosen process to the first initiative.
Reference materialLearning path
Understand existing AI
Actions, access and evidence to organize the next step.
Reference materialLearning path
Operate with the team
Connect service, communication and continuity.
Reference materialLearning path
Decide on deployment
Environment, data and responsibilities in the same conversation.
Reference materialLearning path
Improve with evidence
Turn observation into an improvement whose results are monitored.
Reference materialInteractive example
One claim denial, two perspectives.
Follow an administrative discrepancy between a provider and an insurer, including documents, an exception and a response.
Fictional exampleInteractive example
Healthcare reimbursement: the file before the decision
Link expenses and receipts to identify which items are documented and which need additional information.
Fictional exampleInteractive example
From expense to an organized expense claim
See how a receipt, a justification and a cost center affect the handoff of an expense claim.
Fictional exampleInteractive example
One absence. Two staffing alternatives.
Compare coverage, availability, recorded qualification, room and budget before proposing a change.
Fictional exampleInteractive example
A delay changes the inventory network
Connect demand, reservations, batches and delivery dates to assess a transfer between sites.
Fictional exampleInteractive example
From conversation to a confirmed appointment
Connect preferences, site and schedule. An offered time becomes a booking only after the system confirms it.
Fictional exampleInteractive example
Several tests. One journey that needs to fit.
Explore a test scheduling engine that combines sequence, intervals, site and times, with a separate response for each item.
Fictional exampleInteractive example
The call continues. So does the context.
Voice agents and IVR integrated with Starya’s PBX or the customer’s PBX, with handoff to the team and transfer confirmation.
Fictional exampleGuide · CTO
How do you design a secure architecture for Applied AI?
A roadmap for connecting the operation to enterprise systems with identities, action limits, confirmation, and failure recovery.
PublishedGuide · CISO
What a CISO asks before putting Applied AI into production
How to audit what an AI agent did: connect scope, data, RBAC/ABAC, the audit trail, and recovery in a matrix of controls, evidence, owners, and outstanding items.
PublishedGuide · COO
How to track results and exceptions in an operation with Applied AI
Define completion, responsibilities, and process metrics to track the operation and teams without confusing messages with completed work.
PublishedGuide
Shared SaaS or Dedicated: how to choose a deployment
Compare operations, isolation, networking, data, models, changes, and support. Record requirements, personal data, conditions, and owners, and bring the map to the LGPD assessment.
PublishedGuide
Who is the owner of an AI agent in production?
The owner of an AI agent is a named person, not “the AI”. See what they decide, when they take over, and how to name them before the pilot.
PublishedGuide
AI agents in production in Brazil: how to assess a platform
What to require from a platform or partner to run AI agents in production in Brazil: owner, verification, evidence, integration, deployment, and LGPD.
PublishedGuide
How to build an AI IVR that identifies the member and checks authorization status without hallucinating
How to design an AI IVR that identifies the member, reads authorization status from the source system and hands off with context when it cannot confirm.
Published