AI & Automation Engineering in United States
We engineer production-ready AI systems that go beyond impressive demos to deliver measurable business impact. From custom machine learning models and LLM-powered features to end-to-end workflow automation — every solution is built with reliability, cost control, and scalability at its core.
Why United States Founders Invest in AI & Automation Engineering
The United States remains the world's largest technology market, with Silicon Valley, New York, Austin, and Miami driving global innovation. American founders operate in the most competitive landscape on earth — where execution speed, scalable architecture, and technical excellence are non-negotiable. With venture capital investment exceeding $170B annually and a consumer market of 330M+ users, US-based founders need technology partners who can build infrastructure that scales to meet American-sized ambitions.
What We Build
LLM Integration & Chatbot Systems
We build LLM-powered features that are reliable enough for production use — not chatbots that hallucinate or give contradictory answers. Our approach starts with prompt engineering that is tested against evaluation datasets with hundreds of edge cases. We implement retrieval-augmented generation (RAG) pipelines that ground LLM responses in your actual data, reducing hallucination rates dramatically. Output parsing enforces structured responses so downstream systems can consume AI output programmatically. Conversation memory is managed efficiently to control costs without losing context. We build moderation layers that catch harmful or off-topic responses before they reach users, and escalation paths that route complex queries to human agents seamlessly.
Workflow Automation & AI Agents
We automate the operational workflows that consume your team's time — document processing, email triage, data entry, report generation, approval chains, and customer onboarding sequences. Unlike no-code automation tools that break silently when an API changes, our automations are built in TypeScript with proper error handling, retry logic, and observability. Each workflow is modular and testable, with clear logging that shows exactly what happened and why. We connect your existing tools — Slack, email, CRM, databases, and custom APIs — through event-driven pipelines that trigger reliably and handle edge cases gracefully. AI agents are built with human-in-the-loop checkpoints for high-stakes decisions.
Predictive Analytics & Custom ML
When off-the-shelf models are not enough, we build custom machine learning solutions tailored to your data and business logic. We handle the full pipeline: data cleaning and enrichment, feature engineering, model selection and training, hyperparameter optimization, and deployment behind production APIs. Common applications include demand forecasting, churn prediction, pricing optimization, anomaly detection, and recommendation engines. Every model ships with monitoring for data drift and performance degradation, automatic retraining triggers, and A/B testing infrastructure so you can measure real-world impact before full rollout. We document model behavior, limitations, and failure modes so your team can make informed decisions about when to trust the output.
Document Processing & Data Extraction
We build intelligent document processing pipelines that extract structured data from invoices, contracts, medical records, and other unstructured sources. Our approach combines OCR, layout analysis, and LLM-based extraction to handle the variability that rules-based systems cannot. We implement confidence scoring and human review queues for documents that fall below accuracy thresholds. Output is validated against schemas and delivered to your systems via APIs or database writes. Processing scales horizontally to handle thousands of documents per hour, with cost optimization that routes simple documents to cheaper models and reserves expensive processing for complex cases.
AI Infrastructure & Cost Optimization
AI features that are not cost-controlled become budget nightmares at scale. We build inference infrastructure with semantic caching that serves identical or similar queries from cache, reducing LLM API costs by 60-80%. Smart routing directs simple queries to smaller, cheaper models and reserves expensive models for complex tasks. Rate limiting and token budgets prevent runaway costs from unexpected usage spikes. We implement structured logging for every AI interaction so you can analyze usage patterns, identify optimization opportunities, and demonstrate ROI to stakeholders. Monitoring dashboards show latency, cost per query, accuracy metrics, and user satisfaction in real time.
Why Zulbera Works for United States-Based Founders
Zulbera provides US founders with European engineering precision at competitive rates, without the overhead of a Bay Area or New York development team. We maintain EST and CST timezone coverage for real-time collaboration, use US-based cloud infrastructure (AWS us-east, us-west) for data residency, and deliver with the velocity and quality standards expected by American investors and customers.
Regulatory & Compliance Readiness
We build platforms compliant with US federal and state privacy regulations including CCPA/CPRA (California), state-specific data protection laws, SOC 2 preparation, HIPAA for healthtech, and PCI DSS for payment processing. For fintech clients, we implement frameworks aligned with SEC, FINRA, and state money transmitter requirements.
AI & Automation Engineering in United States — FAQ
Do you work with US-based startups?
Yes. The United States is an active market for Zulbera. We partner with growth-stage founders across major tech hubs including New York, San Francisco, Austin, Miami, and Boston. Our pricing is structured in USD for US engagements.
What timezone coverage do you provide for US clients?
We provide full overlap with EST and CST business hours, and significant overlap with PST. All US engagements include daily async updates and real-time availability during agreed working hours.
Can you build HIPAA-compliant platforms?
Yes. We have experience building healthcare platforms with HIPAA compliance at the infrastructure level — including encrypted data at rest and in transit, audit logging, access controls, BAA-compatible hosting, and PHI handling protocols.
Do you support SOC 2 compliance?
We architect systems with SOC 2 Type II readiness in mind — implementing access controls, audit trails, encryption, incident response procedures, and monitoring that align with SOC 2 Trust Service Criteria. We support clients through their SOC 2 audit preparation.
AI & Automation Engineering in Nearby Markets
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Engagements for AI & Automation Engineering typically start at Engagements typically begin at €25,000 depending on scope and complexity. depending on scope and complexity.
All pricing in USD available upon request.
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