Prototypes that never reach production
The proof of concept impressed everyone, but nobody knows how to wire it into real systems, what each query will cost or who will run it. Months later it is still a notebook.
Service · AI development
AI agent development with LangChain, LangGraph and Amazon Bedrock
AI agent development for teams that need more than a demo: agents and RAG assistants that read your documents, call your systems and run tasks under rules you set. We take them from prototype to production, with the engineers who build them on every call.
We work remotely with companies in the US, Mexico, Peru, Colombia, Ecuador and anywhere else.Where and how we work
On this page
- Task-running AI agents
- RAG assistants over your documents
- MCP servers
- Process automation
- Taking an AI prototype to production
Why so many AI projects stall after the demo
Confident, made-up answers
The assistant states a price, a policy or a deadline that is nowhere in your documents. One hallucination in front of a customer and nobody trusts the tool again.
Sensitive data out of control
Staff paste contracts, customer records or financials into public tools with no idea where the data goes. Without rules or logs, there is no way to know what left the company.
What we build
AI wired into your operations, not a chat window on the side.
Task-running AI agents
Agents that query your ERP or CRM, create orders, update records or send emails through defined steps and permissions, asking a human to confirm when the stakes call for it.
RAG assistants over your documents
Answers grounded in your manuals, contracts, policies or knowledge base, with source citations so anyone can check where the information came from.
MCP servers
Model Context Protocol servers that expose your systems to AI assistants in a controlled way, under the same access rules you already apply to your team.
Process automation
Reading invoices, emails or forms, routing requests and extracting data into your systems, so people stop re-typing information by hand.
Taking an AI prototype to production
Evaluation suites, guardrails, observability and cost controls added to an existing proof of concept, so it can serve real users reliably.
LangChain and LangGraph development
LangChain gives us well-tested building blocks for retrieval, tool calling and model access across providers, so your application is not locked to a single model. LangGraph adds what production agents need on top: explicit state, multi-step workflows, retries, memory and human-in-the-loop checkpoints where a person approves before the agent acts.
We use LangGraph for complex, stateful agents, such as one that gathers data from several systems, drafts a decision and waits for sign-off, and keep simpler chains for simpler jobs. The result is agent behavior you can trace step by step, test and change without rewriting the whole thing.
Amazon Bedrock development
Amazon Bedrock gives access to foundation models from several providers through AWS, inside your own AWS account, alongside the identity, networking and logging controls your team already uses. It is our default when data must stay in your AWS environment or when your organization has standardized on AWS.
We also work directly with the OpenAI and Anthropic APIs when a specific model is the better fit, and we compare options on answer quality, latency and cost per query using your own evaluation data, not vendor benchmarks.
MCP server development
The Model Context Protocol is an open standard for connecting AI assistants to tools and data. We build MCP servers that expose your systems, for example order lookup, ticket creation or reporting, to the assistants your team uses, with each action scoped, authenticated and logged.
Security, access control and query logging
Wherever the use case allows, we deploy in your own cloud account, so prompts, documents and outputs stay in infrastructure you control. Agents only reach the data and actions their role allows, the same way a new employee would.
Every query is logged: what was asked, which sources were used, which actions ran and what it cost. That trail supports audits, makes errors easy to find and lets us improve the system with evidence. Before launch, each assistant is evaluated on real questions from your business, including the ones it should refuse.
- Deployed in your own cloud account
- Role- and action-level access control
- Logs of queries, sources and cost
From use case to production agent
Before we quote the build, you click through your system in a prototype. After that, you see progress every week. No surprises.
We learn your business
Discovery meetings to understand your business and the features you need, before we propose anything.
- You get:
- A requirements document with the agreed scope.
- Typical time:
- 1–2 weeks
Clickable prototype
Click through your system's screens and validate every flow before any code is written.
- You get:
- A clickable prototype to share with your team.
- Typical time:
- 1–2 weeks
Quote with options
A phased proposal with alternatives, so you choose the scope and budget that fit.
- You get:
- A detailed phased quote, with discovery and the prototype deducted.
- Typical time:
- 2–3 days after prototype approval
Phased development
We build in phases and show you working software at the end of each one.
- You get:
- A demo per phase, a short weekly update and a test environment to watch your system take shape.
- Typical time:
- Set in the quote
Testing
We test every flow, and your team signs off before anything goes live.
- You get:
- A release ready for your approval.
- Typical time:
- Set in the quote
Launch and handover
We launch your system or app, train your team and hand over every account.
- You get:
- Servers, app store listings and domains in your name; the code and design are yours once paid in full.
- Typical time:
- Set in the quote
Warranty and support
Every project comes with a 60-day warranty. After that, you choose how we continue.
- You get:
- Free fixes during the warranty, then a monthly plan or hourly support.
- Typical time:
- 60-day warranty, then ongoing
See the full process
Warranty, changes and common questions.
Our AI stack
Agent frameworks, models from several providers and vector stores, chosen for your data, your cloud and your budget.
Artificial intelligence
- LangChain
- LangGraph
- Amazon Bedrock
- OpenAI API
- Anthropic API
- MCP
- pgvector
- Pinecone
Cloud and data
- AWS serverless
- Terraform
- AWS CDK
- Docker
- Kubernetes
- PostgreSQL
- Supabase
- Redis
- MongoDB
AI agent development FAQ
LangChain, LangGraph or Bedrock Agents: which do you use?
It depends on hosting, control and your team. We use LangGraph for complex stateful agents and Amazon Bedrock when data must stay in your AWS account; the two also work together.
Can you take an AI prototype to production?
Yes. We add evaluation, guardrails, observability and cost controls, and connect it to your real systems with proper permissions. Like every project, it has a 60-day warranty: if something we built does not work as agreed, we fix it at no cost.
Do you build MCP servers?
Yes, to expose your systems to AI assistants under your access rules, with every action authenticated and logged.
Is our data used to train models?
We work with business offerings such as Amazon Bedrock and the OpenAI and Anthropic APIs, whose published terms state that customer data sent through them is not used to train their models by default. We still check each provider’s current terms for every project and walk you through them before we start.
Can the agent connect to our existing systems?
Yes. We connect it to your ERP, CRM and other services through their APIs, or build those APIs when they do not exist yet.
API integrationHow do you work with companies in other countries?
We work remotely with companies anywhere, on UTC-5 all year, and bill in USD. We can work in English or Spanish, with video calls, shared tools and deliveries you can try yourself.
Related services
API integration
Payment gateways, ERPs, e-invoicing and third-party services connected without friction.
Custom software
Systems designed around how you operate, not adapted templates. We automate processes and connect your team.
Ecuador
An engineering partner in a nearby time zone that bills in dollars, works in English and ships often.
Nearshore Latin America
A partner in a nearby time zone: live calls, same-day demos and decisions that keep moving at your pace.
Tell us which process you want to automate
Send us a short note on the repetitive task that eats your team’s time, and we will reply with the next steps to assess it.
We work remotely with companies anywhere. Our team is based in Quito, Ecuador; in-person meetings in Quito on request.