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Agentic AI

Asystemthattakesthenextthreesteps,notjustthefirstanswer.

A language model that plans, calls tools, and completes multi-step work, with guardrails you control. $3,999/mo retainer.

See AI Development→
TechnologyAgentic AI Development$3,999/mo
  1. Scope
  2. Build
  3. Evaluate

monthly retainer

Who this is for

You need something to do a job end to end, not just answer a question. A single response from a model is not enough when the actual work is look something up, decide what it means, then take an action based on that. I build agentic systems: language models wired to tools, with planning and guardrails, that carry a task through multiple steps instead of stopping at the first answer.

The pain today

  • A basic chatbot can describe the next step but cannot take it
  • Multi-step processes still need someone to copy an answer from one tool into another
  • No visibility into why a system took an action once it starts acting on its own
  • A single bad step can cascade if nothing checks the work along the way
  • Off-the-shelf agent builders stop at the first tool your process does not already support

The outcome you get

  • A model wired to your tools that plans, acts, and reports what it did
  • Guardrails that stop or escalate before a low-confidence action goes through
  • A full log of every step taken, so any action can be traced back to its reason
  • Human checkpoints placed where a mistake would actually cost something
  • A system built for your actual tools, not limited to a builder's preset list

What makes a system finish the job, not just describe it

A conversational model answers a question and stops. A system built for multi-step work takes a goal, breaks it into steps, calls the tools needed to complete each one, and checks its own progress before deciding what to do next. The difference is not the model itself, it is the loop wrapped around it: plan, act, observe, decide again.

That loop is where the real engineering work sits. A model that can technically call a tool is not the same as a system that calls the right tool at the right time, recovers cleanly when a call fails, and knows when to stop and ask a person instead of guessing.

A model wired to your tools that plans, acts, and reports what it did

Where autonomy needs a guardrail

Full autonomy sounds appealing until the system takes a wrong action with real consequences: sending a message that should not have gone out, writing to a record that should have stayed untouched, spending money it should not have spent. Every build I deliver has explicit boundaries: which actions run automatically, which need a confidence threshold cleared first, and which always stop for a person to confirm.

Those boundaries are a design decision made with you before a single line of code runs, not an afterthought bolted on after something goes wrong.

+500%: Lead base growth.
Norte Web Digital

Proof this holds up outside a demo

I built the CRM behind Norte Web Digital's lead pipeline, which uses Claude AI to process inbound activity from Google Maps and route it through WhatsApp automatically. The result: a lead base that grew by over 500%, with 250 new leads a day flowing through the pipeline and a lead-to-client cycle of three to four days. That is what this kind of pipeline looks like once it is carrying real commercial weight instead of answering a single prompt.

Where this fits, and where it doesn't

This approach is the right tool when a task genuinely has multiple steps and a decision point between them: qualifying a lead and routing it, reading a document and updating three systems from it, monitoring a queue and escalating what needs a person. It is the wrong tool for a task that is really just one lookup or one answer, where a simple grounded response does the job at lower cost and lower risk.

Part of the first conversation is figuring out honestly which category your task falls into, before committing a retainer to build the more complex version.

Pricing, delivery, and ownership

Agentic AI development runs under the AI Development retainer at $3,999 a month. Work lands in cycles of two to four days, with daily async updates and a response inside 24 hours. The engagement carries a 14-day money-back guarantee, and you can cancel anytime after. Every tool connection, every guardrail, and every line of code is yours under Work Made for Hire terms from the day you pay.

Recent proof

A comparable engagement, delivered and documented.

+0%Lead base growth
Custom CRM · WhatsApp + AI

A custom CRM that turned Google Maps into a lead machine

A custom CRM that captures leads from Google Maps, reaches them via WhatsApp, and uses AI to suggest replies. Lead base grew over 500%, 250 new leads a day.

Read the case study

Keep reading

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The same work, framed for a different situation.

Browse by technologyOne senior engineer building the system, not a rotating account team.Work that gets finished end to end, not just described.Built for the one thing your business actually does differently.A feature built from scratch around what your business actually produces.Drafts and summaries that live inside what you already use, not a separate tab.

Frequently asked questions

The questions prospects ask before they book.

It is a system built around a language model that does not stop at one answer. It plans a sequence of steps, calls the tools it needs (a database, an API, a messaging platform), checks the result, and decides what to do next, until the task is actually finished.

Guardrails set before the build starts. Some actions run automatically because the cost of a mistake is low. Others need a confidence threshold cleared, or stop entirely for a person to confirm before anything happens. Which category an action falls into is a decision we make together up front, not something guessed at afterward.

Yes. Every step the system takes is logged: what it decided, what tool it called, and what came back. If an action needs to be traced or questioned later, the reasoning is there, not lost.

Traditional workflow automation follows a fixed path: if this, then that. This approach reasons about what to do at each step rather than following a rule someone wrote in advance. It is a better fit when the path genuinely varies case to case, and a worse fit when your process really is a fixed sequence a simple automation already handles well.

Whatever your process actually uses: a CRM, a messaging platform, an internal database, a third-party API. I build against your real tools rather than limiting the system to whatever a pre-built agent builder happens to support.

The AI Development retainer is $3,999 a month, with work landing in cycles of two to four days rather than a single delivery months out. There is a 14-day money-back guarantee, and you can cancel anytime after that.

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Adriano Junior

Senior Software Engineer & AI (LLM) Engineer. 17+ years building websites, apps, and AI that launch.

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