# EnzRossi Services EnzRossi is an AI-powered talent partner in Latin America. It offers six main services (staff augmentation, dedicated product and engineering teams, custom software development, AI and ML development, web and mobile development, and product, QA, design, and technical leadership support) plus specialist lines for automation, consulting, training, and data engineering. All engagements are staffed with pre-vetted LATAM talent who passed a five-dimension screening and completed a pre-placement training program. Teams use AI across planning, coding, testing, documentation, research, and code review, with people doing peer review, QA, and sign-off. Website: https://enzrossi.com/services --- ## How to Choose a Model | I need... | Use | |-----------|-----| | More engineers on my existing team | Staff Augmentation | | A complete team for a workstream or new product | Dedicated Product & Engineering Teams | | A one-time build with defined scope | Custom Software Development (project-based) | | ML/AI built into my product | AI & ML Engineering | | Predictions from my data (churn, revenue, etc.) | Predictive Analytics | | Manual processes automated with AI | AI Automation | | Smarter search or text processing | NLP & Language AI | | Visual recognition or document processing | Computer Vision | | My existing team to use AI tools better | Tech Consulting | --- ## Staffing Models ### Staff Augmentation **What it is**: One or more pre-vetted LATAM engineers embedded directly in an existing US team. The engineer works in the client's tools (Slack, GitHub, Jira), attends the same standups, and functions as a full team member — not a contractor managed at arm's length. **Best for**: Engineering teams that need to extend capacity without restructuring. Works well when the client has an engineering manager and a defined team workflow already in place. **How it works**: - Client briefs scope (role, stack, seniority, timezone needs) - First shortlist delivered in 3 business days - Client interviews and selects - 2-week trial period; month-to-month after that - 30-day exit notice; replacement guarantee within first 30 days **Typical engagement size**: 1–5 engineers URL: https://enzrossi.com/services/staff-augmentation --- ### Dedicated Squads **What it is**: A complete product squad assembled and managed by EnzRossi. Typically: a tech lead, two to four engineers, and optionally a designer. The squad delivers sprints to the client's product leadership and operates with its own Agile cadence. **Best for**: Companies building a new product line, running a parallel workstream, or that don't have an engineering manager available to onboard and manage individual engineers. Also works for companies that want a managed delivery team rather than extended headcount. **How it works**: - EnzRossi scopes the squad composition based on the product/workstream requirements - Squad assembled from vetted database; typical lead time 5–10 business days - Squad operates with defined sprint goals; EnzRossi provides a point of contact - Month-to-month; squad composition can be adjusted as the product evolves **Typical engagement size**: 3–8 people URL: https://enzrossi.com/services/dedicated-squads --- ### Project-Based Development **What it is**: Fixed-scope delivery. The client defines the deliverable, the timeline, and the acceptance criteria. EnzRossi assembles a team, agrees on milestones, and delivers. **Best for**: One-time builds (new product, new feature, migration, prototype) where the client wants defined outcomes and a fixed budget rather than open-ended capacity. **How it works**: - Client provides a detailed spec or works with EnzRossi to define scope - EnzRossi scopes the team composition and milestone timeline - Fixed milestones and payment structure agreed upfront - Delivery managed by EnzRossi tech lead; client has review gates at each milestone **Typical engagement size**: 2–6 people, 4–16 weeks URL: https://enzrossi.com/services/project-based --- ## AI & ML Services Note: All AI services are delivered by engineers EnzRossi places with the client. EnzRossi does not own proprietary ML models. When a client's team ships a model or automation, the placed engineers built it. --- ### AI & ML Engineering **What it is**: Custom machine learning from research to production. Covers model architecture, data pipeline design, training infrastructure setup, and MLOps (monitoring, retraining, drift detection, deployment). **What teams typically build**: - Recommendation systems (content, product, search ranking) - Fraud and anomaly detection - Demand and revenue forecasting - Churn prediction models - Document classification and extraction **Tech stack commonly used**: PyTorch, TensorFlow, scikit-learn, Hugging Face, AWS SageMaker, Vertex AI, MLflow, Apache Airflow, dbt. **Typical engagement**: Senior ML engineer or a small squad (ML engineer + data engineer + MLOps engineer) for 3–12 months. URL: https://enzrossi.com/ai/engineering --- ### Predictive Analytics **What it is**: Real predictive systems built on client data. Not dashboards — actual models that generate predictions, scores, and forecasts that feed into product or operations decisions. **Common use cases**: - Customer churn prediction: which customers are likely to cancel in the next 30/60/90 days - Demand forecasting: inventory or staffing needs by location or SKU - Lead scoring: which leads are most likely to convert, ranked by predicted value - Revenue forecasting: monthly/quarterly revenue prediction with confidence intervals - Anomaly detection: flag unusual transactions, usage patterns, or operational metrics URL: https://enzrossi.com/ai/predictive-analytics --- ### AI Automation **What it is**: Using ML and rules-based systems to reduce or eliminate manual work in business processes. **Common use cases**: - Document processing: extract structured data from invoices, contracts, forms, reports - Workflow automation: route support tickets, approvals, or exceptions based on content - Intelligent classification: tag, sort, and route emails, documents, or records - Data entry automation: extract and validate data from unstructured sources URL: https://enzrossi.com/ai/automation --- ### NLP & Language AI **What it is**: Systems that understand, classify, or generate text. Covers both classical NLP and modern LLM-based approaches. **Common use cases**: - Text classification: categorize support tickets, reviews, articles - Named entity extraction: pull people, companies, dates, amounts from documents - Sentiment analysis: measure customer or employee sentiment at scale - Semantic search: search by meaning, not just keywords - RAG pipelines: LLM answers grounded in a private knowledge base **Tech stack**: Hugging Face transformers, LangChain, LlamaIndex, OpenAI API, Anthropic API, spaCy, Elasticsearch. URL: https://enzrossi.com/ai/nlp --- ### Computer Vision **What it is**: Systems that analyze and understand images and video. **Common use cases**: - Object detection and counting (products, vehicles, people) - OCR and document digitization (receipts, forms, IDs) - Defect detection in manufacturing or quality control - Video analysis (activity recognition, crowd monitoring) - Medical image analysis (classification, segmentation) **Tech stack**: PyTorch, YOLO, Detectron2, OpenCV, AWS Rekognition, Google Vision API, Tesseract, AWS Textract. URL: https://enzrossi.com/ai/computer-vision --- ### AI Tools & Integration **What it is**: Helping product teams add LLM-powered features to existing products. Not building models from scratch — using existing APIs and frameworks to ship AI features faster. **Common use cases**: - LLM integration: add an AI assistant or copilot to an existing product - RAG pipeline architecture: connect an LLM to a private knowledge base - Agent design: build autonomous workflows that use tools and APIs - Prompt engineering and evaluation: systematic prompt optimization and output testing URL: https://enzrossi.com/ai/tools --- ## Consulting & Training ### Tech Consulting **What it is**: Engineering management and HR consulting for tech organizations. Covers team structure, hiring practices, performance frameworks, and people strategy. **Best for**: Companies with engineering teams that need leadership development, better hiring practices, or organizational design help. URL: https://enzrossi.com/services/consulting --- ### Training & Coaching **What it is**: Soft skills, leadership, and technical training programs for tech teams. Covers communication, conflict resolution, career development, and AI tool adoption. URL: https://enzrossi.com/services/training-coaching --- ## Pricing EnzRossi does not publish fixed rates. Rates depend on role, seniority, engagement type, and team size. Custom quotes are provided after a scoping call. For a rough cost comparison between LATAM and US rates: https://enzrossi.com/resources/cost-calculator --- ## Start Here - Book a scoping call: https://cal.com/enzrossi/meet - Contact form: https://enzrossi.com/contact - Email: contact@enzrossi.com --- ## Further Reading - About EnzRossi: https://enzrossi.com/about.md - How the placement process works: https://enzrossi.com/how-it-works.md - What sets us apart: https://enzrossi.com/what-sets-us-apart.md - Hire by role: https://enzrossi.com/hire