Autonomous Agents

When answering isn't enough

Some requests need work done, not information returned. Autonomous Agents take a task and run it — multiple steps, real tools, until it's finished — then report back inside the same conversation.

When to use an Autonomous Agent

The AI Agent Platform already calls your systems directly through custom functions. That's the right tool when the work is one known request to a known API — checking an order, looking up a balance, creating a ticket. It's fast, predictable, and cheap.

Autonomous Agents are for the work that doesn't fit that shape: multi-step tasks that use the same tools a person would, in situations where no integration exists.

Order status from a supplier with no API. Your supplier has a portal and a login, and no integration on their roadmap. The agent signs in, finds the order, reads the status and tracking, and reports back — in the conversation where a customer asked, or on a schedule into your own systems. You stop waiting for someone else's engineering team.

Research compiled across dozens of sources. Give it a question and a scope. It searches, reads across as many sources as the task needs, cross-references what it finds, and writes the result up as a document. Competitor pricing, regulatory changes across jurisdictions, background on a list of accounts — work that would take an analyst a day.

Automated testing for sites and software. Point it at an application and describe what should happen. It drives a real browser through the flow, runs the checks, and reports what broke — on demand, on a schedule, or after every deploy.

Need the same data again next month rather than once? That's a standing feed - see Web Data.

You decide what gets delegated. Hand work to an Autonomous Agent always, only on certain channels, on keyword match, or let the AI classify intent and decide. Nothing runs autonomously unless you configured it to.

Not every task starts with a customer. Agents also run on a schedule, on a recurring trigger, or on a call to the API - for the work that happens whether or not anyone asked.

Three capability tiers. Basic — knowledge base search, web search, web fetch, and reply. Standard — adds file handling and a full skill library. Premium — adds shell execution and browser automation.

Locked down by default. Allowlist or blocklist individual tools and skills per agent, on top of the tier. Scope memory per agent, per conversation, or per user. Enterprise workloads run in dedicated isolated containers.

A person is always reachable. Human handoff is available at every tier and cannot be filtered away.

See exactly what it did. Every task keeps a reviewable record — the steps it took, the tools it used at each one, and what came back. Watch a task while it's running, cancel it mid-flight, or open it afterward and trace how it reached its answer.

Autonomous work lands in the same audit trail as the rest of the platform, reviewable by the same people under the same policy. There's no separate system to check and nothing that happens off the record.

Predictable cost, by design. Autonomous work is metered per task, with per-account concurrency caps and per-task timeouts you set. Token usage is tracked against the same allowance as the rest of your platform, so agent work shows up on the same bill and the same report — no separate surprise line.

It fails safe. If a task doesn't complete, the conversation falls back to a standard AI response rather than leaving the customer stranded.

Your keys, your models. Bring your own LLM key and choose your model per agent, with system defaults as fallback.

FAQ's

How does pricing work?

You buy a bundle sized to your business, priced on three dimensions: the feature set you enable, the number of domains you cover, and your monthly token allowance. We bill overages only when you exceed the bundle, and every overage is itemized. See our pricing page for full detail.

How many AI Agents can I have?

Our team will assess your business processes, goals, and challenges to determine how many you need for your solution. We'll recommend strategies that align with your objectives, making sure you're set up for success and growth.

What results can I expect from Nuestra AI solutions?

With the right Nuestra AI tools, you can expect increased operational efficiency, cost savings, and improved customer satisfaction. We focus on delivering measurable results that align with your business goals, such as higher customer satisfaction rates and improved productivity.

Will I receive ongoing support after implementing the solutions?

Yes! We, with a signed contract, provide continuous support and optimization after implementation to ensure your generative AI tools are functioning effectively and providing the results you need. Our team is here to help you adapt and grow as your business evolves.

How long does it take to see results with Nuestra AI solutions?

The time to see results can vary based on the complexity of your needs and the AI tools implemented. However, many businesses begin to experience noticeable improvements in efficiency and performance within a few weeks to a couple of months after integration.

With the AI Agent Platform, where do lead notifications go?

That depends on your business needs. Because we meet with you to find out what integrations are important to you, we can customize the destination of the lead notifications. Do you want to integrate with your CRM? We can do that.

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What happens if we exceed our included usage?

You'll get an alert as you approach the limit, and overages are trued up quarterly rather than billed the instant you cross a line. Every overage is itemized by product, model, and outcome.

Can we self-host?

Yes, under an enterprise agreement. Hosted deployment is the default.

What's your uptime commitment?

It depends on your support tier: 99% on Priority and 99.9% on Enterprise, with service credits on Enterprise. Both are measured outside scheduled maintenance windows, which are set out in your service agreement. Standard carries a target rather than a commitment. See the pricing page for the full comparison.

Where does our data live, and who can access it?

Your data resides in US datacenters. Which cloud — Microsoft Azure, Amazon Web Services, or Google Cloud — is selected as part of your contract.

Within your account, access is yours to control: role-based permissions, per-user assignment at the agent level, and API keys scoped by resource with separate read and write rights. Every write is recorded in an audit trail at both account and agent level.

Our own staff access your data only to resolve a support issue or investigate an incident, only with your permission, and only for the duration of that ticket. If you'd rather not approve each request individually, standing defaults can be set up for your account.

Which model providers does the LLM Router support?

OpenAI, Anthropic, Google, Groq, Mistral, Cohere, DeepSeek, Bedrock, Azure OpenAI, and OpenRouter, plus local deployments through Ollama, vLLM, and LM Studio.

What happens when the AI can't answer a customer?

The conversation escalates to a person — routed by intent, skill, and language — carrying the full transcript, the customer record, and anything the agent already collected. Your team picks up mid-conversation instead of starting over.

Is web data collection legally reviewed?

Collection runs against the sources and identifiers you provide and covers publicly accessible data only. We honor robots directives and document the source and collection method for every field we deliver, so your legal team can review provenance before you build a process on top of it.

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