Cognitive Architecture
Building multimodal pipelines with orchestrated agents, API Gateway, Lambda, and DynamoDB — 100% serverless.
Cognitive Engineering and Serverless AI in action
Creation, orchestration, and integration of intelligent cloud systems — from conception to complete automation.
WHAT I DELIVER
(EASY AND FAST)
AI & Automation Consulting
Developing intelligent workflows integrating OpenAI, Salesforce, LinkedIn, and other ecosystems.
Multimodal UIs
Voice, touch, and text interfaces with unified cognitive flow and usage metrics.
Data & Performance
SEO, CRO, and analytics automation to increase impact, efficiency, and operational intelligence.
DevSecOps & Observability
Automated deployments, CI/CD, logs, and real-time monitoring with CloudWatch and continuous security practices.
Multi-Agent Orchestration
Creation of autonomous intelligences cooperating with each other to generate, test, and scale products cognitively.
Architectures that I implement
I sell architecture and deployment of complex environments on AWS, using my AI and methodology.
🟢 Base Serverless (48h)
API Gateway + Lambda (Python) + Cognito + DynamoDB + S3/CloudFront + SAM. Ready to authenticate, log in, and scale in the Free Tier.
🤖 AI API in Production
Inference with OpenAI/Bedrock, quotas, caching, cost-per-request metrics, and security controls.
🗂️ Data & Serverless ETL
S3 + Glue + Lambda + Step Functions for low-cost analytical ingestion, cleaning, and availability.
🏷️ Baseline SaaS Multi-tenant
Tenant separation, RBAC, limits, and observability. Ready for pay-as-you-go billing.
🔌 Corporate Integrations
Salesforce, LinkedIn, webhooks, queues, and events. Connectors with retries and DLQ.
🛡️ Observability & Security
CloudWatch dashboards, alarms, WAF, minimal IAM, backups, and cost policies.
About me
Specialist in AI, Data, and Performance — AI system architect THRIVE9X. A hybrid professional in Digital Marketing and Artificial Intelligence, focused on transforming data into measurable, scalable, and sustainable growth.
My performance connects machine learning, intelligent automation, CRO and UX to create scalable systems that combine creativity, data, and technology. As creator of THRIVE9X, I developed a modular AI framework that integrates autonomous agents, predictive analytics and mechanisms of continuous optimization in real time.
The project began as an independent laboratory where I apply and test strategies that combine AI and performance, helping brands and professionals optimize conversions and decisions with precision.I believe in the intersection between data intelligence., empathy and conscious automation — building bridges between strategy and execution.
Applied AI that I master + Stacks and Connectors
Ready for the next level?
I accelerate your environment in 48 hours with Free Tier-first and Pluggable AI Layer.
Recent cases
A few examples of how I use THRIVE9X + AWS to move beyond slides and put AI into production — fast, safe, and within the Free Tier whenever possible.
Course platform from zero to live
- API Gateway + Lambda (Python) + Cognito + DynamoDB + S3/CloudFront
- Single
/ai/inferendpoint for class summaries and student questions - Logs, metrics and alerts in CloudWatch to track real usage
* Product team went from PPT to a testable environment with real students.
Multi-AI router for growth squads
- /ai/infer layer with connectors for OpenAI, Bedrock, Claude, Grok and custom endpoints
- Secrets Manager + quotas and rate limiting per user/team
- Telemetry for cost, latency and provider used per request
* Switch AI provider without rewriting the backend — just via configuration.
Multi-tenant baseline ready to scale
- Dev/stage/prod environments with CI/CD and cost tags per tenant
- DynamoDB partitioned by tenant + RBAC via Cognito
- Pluggable AI to generate insights inside the product
* Product goes from fragile MVP to production-grade base with observability.
Risk monitor with auditable AI
- Data ingestion into S3 + processing with Lambda and Step Functions
- AI model (via Bedrock/OpenAI) generating risk signals with explainable context
- Structured logs for compliance and decision review
* Team spends less time building spreadsheets and more time deciding.
Smart offer engine on top of checkout
- Funnels mapped in DynamoDB with events from the payment gateway
- AI suggesting upsell/cross-sell and personalized messages in real time
- Simple performance dashboard via CloudWatch + lightweight panel
* Higher average ticket without rewriting the e-commerce from scratch.
CS copilot with churn prioritization
- Usage logs ingested into S3 + Lambda generating engagement signals
- AI classifying accounts by risk/opportunity and suggesting next actions
- CRM integration to trigger automatic tasks for the CS team
* CS stops working “in the dark” and starts operating with an AI radar.
How I run projects with THRIVE9X + AWS
- Fast discovery: I map the minimum case that proves value (POC, pilot or lean PROD).
- Free Tier-first architecture: I start with the lowest possible cost, already thinking about scale.
- Infrastructure as code: everything versioned (SAM/CloudFormation/IaC) to replicate and evolve.
- Pluggable AI layer: connectors for multiple providers without coupling to the product.
- Real handover: video, documentation and clear acceptance criteria for the internal team.
Each case starts small, but already prepared to become a product or critical operation without starting over.
Sprint 48h —From 0 to launch
🧠 What do you get
Infrastructure base with API Gateway + Lambda (Python) + Cognito + DynamoDB + S3; deploy via SAM; basic login; logs; domain and SSL; Free Tier cost guide; Plugable AI Layer.
- Infrastructure as code + organized repository
- Initial observability + alarms
- Handover with 15-minute video
- Warranty if not deployed within scope, no setup fee
Acceptance criteria:
- Domain + active SSL/ACM
- Cognito Login functional
- Endpoint
/ai/inferresponding - Logs + alarms basic
- Handover 15 min recorded
⚙️ Plug-in AI Layer/span>
- Ready-made connectors (toggle) for OpenAI, Bedrock, Grok etc. via endpoint
/ai/infer - Secrets in Secrets Manager + variables per environment
- Rate limit and quotas per user/tenant
- Standardized schema (input, context, tools, output)
- Telemetry (request_id, latency, tokens/cost)
- Fallbacks and retries with exponential backoff
- Prompt templates, guardrails and cache
- End-to-end authorization (Cognito → policy on the IA endpoint)
Switch AI without rewriting the backend.
🧩 Prerequisites
- Domain (or subdomain) DNS access
- Project logo and name
- Technical owner and business decision-maker
- API keys (if any integrations)
No domain? We'll create a temporary subdomain.
✅ Guarantee & Comparison
- Deadline Guarantee: if it doesn't go up in scope, no setup fee
- Less than 1/5 the cost of a sprint with a squad
- Free Tier-first: near-zero cloud cost at the start
Your environment in 48 business hours. No pain, no hype — just delivery.
Plans and investments
48-hour Sprint — Functional Proof of Concept
$ 2418,72
- API Gateway + Lambda (Python) + Cognito + DynamoDB + S3/CloudFront + SAM
- Domain + SSL/ACM, CORS and minimal IAM
- Pluggable AI boilerplate with single inference endpoint
- CloudWatch logs + alarms, handover with 15 min video
- Free Tier-first: cost and limits guide
For those who need proof in days, not weeks.
Book Sprint7-Day Pilot — Real Use Case
$ 5459,03
- Complete Flow (Ingestion → Inference → Return)
- Quotas, Caching, and Hardened Security (Private Routes, Optional WAF)
- Defined Success Metric (SLA/Latency, Cost/Req, Accuracy)
- Mini-dashboard with Metrics and Alarms
For those who will show to management/clients or operate a paid pilot.
Start PilotPROD 21 days — Scale
$ 14–17 k
- Multi-environment (dev/stage/prod) + Full CI/CD
- Advanced observability (traits, metrics, cost per feature/tenant)
- Cost optimization (limits, schedules, lifecycle policies)
- Hardening: backups, log retention, compliance tags, playbooks
Public range; for compliance/sector, adjustment upon request.
Talk about PROD
Less than 1/5 of the cost of a sprint with a squad. Price transparency — no hidden fees.Assumptions: base scope (API Gateway, Lambda, Cognito, DynamoDB, S3/CloudFront, SSL/ACM and /ai/infer).Advanced integrations/SSO/compliance are included in the Pilot/Production phases.
Solicitar proposta
Deadline Guarantee
If the environment does not come up within the 48-hour Sprint scope, you will not pay the setup fee.
Advantage TJ
Market: $ 5K-17k In 3 weeks with a squad of 6 specialists. My Sprint: 48h, $ 2,428.33, Free Tier-first.
FAQ
Will Free Tier drive up costs?
I provide pre-configured limits and alerts, along with a capacity guide and guidance on when to migrate.
How will security be affected?
Minimum IAM, CORS, SSL/ACM, logs; optional WAF in Pilot/Production.
I don't have a frontend ready.
I'm including a lightweight frontend in S3 with a base theme. It can be replaced later.
Which AI providers are supported?
OpenAI, AWS Bedrock, Azure OpenAI, Hugging Face Inference, SageMaker/own endpoint, Grok and “bring your endpoint” (REST/gRPC).
How do I choose a provider? (OpenAI, Bedrock, Grok...)?
You choose by tenant/user/plan. The router reads the provider from headers, Cognito claims, or environment variables. Switching providers does not require changing the product code.
What variables/secrets do I need?
I use AWS Secrets Manager. Examples: OPENAI_API_KEY, AZURE_OPENAI_KEY, BEDROCK_MODEL, HF_API_TOKEN, SAGEMAKER_ENDPOINT, GROK_API_KEY, GROK_BASE_URL, GROK_MODEL. I also configure AI_PROVIDER as a standard for the environment.
Is it possible to add another AI provider?
Yes. I create a new adapter that speaks the same "dialect" as the endpoint. /ai/infer, I register it on the router and enable it through configuration. I include metrics, quotas, and fallbacks.