No demos. No slide decks. Real systems in real businesses across the United States, Colombia and Mexico.
I'm Carlos Betancur Gálvez, founder of btodigital and one of the leading specialists in implementing AI with Claude (Anthropic).
An AI consultant with Claude is a specialist who designs, builds and ships production systems on top of Anthropic's Claude models, rather than selling generic "AI strategy." In practice that means WhatsApp and chat agents, RAG systems over your own documents and CRM, process automation, and CRM/ERP integrations, engineered on cloud infrastructure with real observability, security and predictable costs, not just a demo.
Model choice isn't ideological. It's strategic. For the enterprise use cases I see most, Claude offers three concrete advantages that end up making the difference in production.
In practice, my architectures are usually hybrid: Claude for primary reasoning and conversation, Gemini Flash for cheap high-volume batch processing, and open models on GCP when extreme privacy or minimal latency is required. The question isn't "which model is best?" but "which combination solves this specific problem at the lowest possible cost?".
I combine one public case that lives on this very domain with five enterprise projects under NDA, presented by industry with technical detail and outcome.
What it does: greets anyone who messages my WhatsApp, replies in real time, identifies the lead's intent, qualifies them as A, B or C, sends PDF books, follows up when a conversation goes quiet, and escalates to me by email when someone wants to book a meeting.
Technical stack: Claude Sonnet 4.6 + Gemini 2.5 Flash + Firestore on Cloud Run, integrated with Kapso for the WhatsApp Cloud API. RAG over 500+ proprietary documents, audio support, a three-stage follow-up system (30 minutes, 3 hours, 6 hours), and quiet-hours respect (no messages between 10 p.m. and 7 a.m. Colombia time).
Result: operating cost between USD 5 and 8 per month. It captures, qualifies and routes leads 24/7 with no human intervention. Try it by messaging on WhatsApp →
A vertical healthcare platform with 400+ published physicians. I built a system that automatically translates Google My Business reviews into English with Claude, generates personalized landing pages for VIP doctors with i18n, and monitors Google Ads campaigns daily with Cloud Run Jobs and smart alerts that notify when performance drops.
Stack: Express + Tailwind + Firestore + Cloud Run on GCP, Resend for transactional email, Vertex AI for batch processing.
A multi-tenant platform that listens to recordings of in-store salesperson conversations and measures service quality with AI. It detects whether they greeted the customer, asked the right questions, handled objections, and closed cross-sell opportunities. The first client operates three locations in Medellín; the product is designed to scale to any retailer with in-person sales staff.
Stack: OpenPlaud fork + Vertex Gemini 2.5 Flash + Firestore + Google Login authentication. Processes hours of audio daily in batch.
Two-way sync between Bitrix24 and BigQuery every 12 hours for a leading industrial company in Latam. Executive dashboard in Next.js + Firebase with AI analysis over the sales funnel. We process around 50,000 historical deals to identify closing patterns, abandoned leads and churn.
Stack: Cloud Run Job + Cloud Scheduler for ETL, Firestore as operational cache, Vertex AI for analysis, Next.js + Firebase for the frontend.
An electronics distributor with a large catalog needed to sync Shopify with Microsoft Dynamics 365. I built middleware with paid-order webhooks, real-time shipment tracking updates, dual-SKU handling, and automatic fallback to Pub/Sub queues with exponential retry when the ERP doesn't respond.
Stack: Node.js on Cloud Run us-central1, Pub/Sub, Firestore, integration with Shopify and Dynamics APIs.
With my guidance, a services company built an internal assistant that answers questions about procedures, active contracts, internal policies and past cases. RAG over 2,000+ documents. It reduces the time the team spends hunting for scattered information and frees up the back-office.
Stack: Claude + Vertex embeddings + Firestore Vector Search + web interface in Astro.
I've built RAG systems connected to platforms like HubSpot, Clientify, Klaviyo, Shopify and WordPress so marketing and sales teams can query their own data in plain language: customer history, audience segments, campaigns sent, purchase behavior. The team asks and the system answers with real data, not generic model generalizations.
Stack: Claude + Vertex AI embeddings + Firestore Vector Search + incremental sync via webhooks and each platform's REST APIs. The index updates automatically as CRM records change.
I don't just advise: my team at btodigital and I design, build and maintain AI SaaS products. Some are paid; six are completely free so you can see the quality before you talk to me.
An AI SEO agent that audits WordPress sites, identifies keyword opportunities, generates optimized articles and publishes them automatically. It replaces hours of manual work from an entire SEO team.
An official app published on the Shopify App Store that optimizes product titles, descriptions and meta tags with AI. It improves conversion and SEO for stores with large catalogs.
A platform of AI WhatsApp assistants for businesses. It answers, books and sells 24/7 in Spanish, with coexistence (keep your number) and context-aware handoff to your human team. It's the productized version of what I build custom.
Multi-dimensional analysis with PageSpeed, tech stack detection and a Gemini-powered diagnosis of your positioning.
Builds your buyer persona with buying journey, empathy map and messaging framework ready for your marketing team.
A diagnosis of your digital advertising with 25+ signals analyzed by AI. Useful before audits or budget decisions.
A radar chart with industry benchmarking. It shows how far you are from your sector's standard and where your gaps are.
Up to 60 AI-generated ads, ready to publish on Google Ads, Meta Ads or TikTok Ads, with fine-tuned headlines and descriptions.
Plan your editorial calendar with AI. It suggests topics, formats, channels and goals aligned with your industry and buyer persona.
Every tool is fully functional, with no mandatory sign-up and no credit card. If you like them, let's talk about how to build something like this inside your company.
Not every use case fits every industry. These are the patterns that work best in each vertical, based on projects I've executed or advised on over the past few years.
I don't promise magic or 24-hour transformations. A well-executed AI project has clear phases, measurable deliverables, and the ability to stop the process if reality doesn't match the expectation.
An in-depth interview with you and your team. I identify the real problem (not the symptom), assess whether AI is the right solution or whether there's a simpler fix, and deliver a document with three possible paths: ambitious, balanced and conservative. If you don't want to move forward after this, no problem: the diagnosis is yours to keep.
I build a functional but scoped version that proves the solution works in your real context. We test it with a pilot group, measuring quality, cost and adoption. Here we kill bad ideas quickly instead of spending months building something nobody will use.
We take the POC to a robust system: architecture on Google Cloud Platform, observability with Cloud Logging, an alerting system, access controls, error handling and predictable costs. I document everything so your team can maintain or evolve it without depending 100% on me.
AI isn't a project that ends: it's a system you tune. We refine prompts, update the RAG, add capabilities, monitor metrics and adjust costs. This can be a monthly retainer or one-off sessions as needed. You set the pace.
This is one of the questions I most dislike dodging. Here are the real ranges for my projects, in US dollars, so you know whether it makes sense to keep talking.
A 30-minute session over video call or WhatsApp. I help you determine whether your use case makes sense for AI, what order of magnitude it might cost, and what returns are realistic.
A functional but scoped version. Ideal for small businesses with a well-defined use case, or for corporations that want to validate before committing a large budget. Timeline: two to three weeks.
A production system with robust architecture, documentation, observability and a maintenance plan. The vast majority of enterprise projects fit within this range.
Ongoing maintenance, iteration, evolution and support. Variable depending on scope, SLA and the level of involvement from my team.
Anthropic offers its own implementation service (Forward Deployed Engineers) directly out of San Francisco, with rates that typically start at USD 150,000 per project and focus on Fortune 500 companies. My value proposition is to give you the same technical level, applied to your market, at prices 10 to 50 times lower, in fluent English and neutral Spanish, and with an understanding of the local context.
The only essential is a clear use case: a repetitive process, an operational bottleneck, or a conversation you are losing. You don't need perfect data or an in-house technical team; I help you start from scratch. What does help is decision-making at the leadership level: implementing AI well changes processes, it doesn't just add another tool.
A proof of concept (POC) takes two to three weeks. A production-ready implementation takes four to six weeks. In most of the projects I've worked on, the client sees the first signs of savings or commercial impact within the first month. Fine iteration (tuning the prompt, refining the RAG, adding capabilities) is continuous.
I personally lead every project, but behind me is the technical team at btodigital, my agency. Depending on the scope, I bring in developers, designers, and data or paid-media specialists. I always build the strategy and architecture myself: I don't delegate the piece that decides whether the project lives or dies.
Anthropic, the company behind Claude, does not use your API call data to train its models by default. On top of that, in enterprise projects we architect the solutions on Google Cloud Platform with encryption at rest and in transit, IAM-based access controls, and strict tenant separation where applicable. Every project includes its own data retention and deletion policy.
Claude has three concrete advantages for businesses: a huge context window (it processes entire long documents without losing the thread), excellent performance across English and neutral Latin American Spanish, and more mature agentic capabilities for complex workflows. In projects where I've compared Claude with GPT-4 and Gemini, Claude wins on extended reasoning and on following multi-step instructions.
Yes. I handle projects in English and have clients in Miami and other U.S. cities. My site is available in English and Spanish, and both Beta (my WhatsApp agent) and the solutions I build support both languages natively. Projects are managed remotely.
I work with both. My pricing model is designed so that a small business with a well-scoped project can have AI in production for under USD 10,000, while I also run corporate projects worth several tens of thousands of dollars. The difference is not the size of the client but the depth of the problem and the complexity of the integration.
Three paths depending on where you are. I answer personally.
A 30-minute session over WhatsApp. I answer personally, assess your case, and tell you whether it makes sense to keep talking.
My track record, credentials, full portfolio, and the projects I've built over 15 years.
58+ articles on AI with Claude, digital marketing and medical marketing. New ones every week.