Quantum Leap builds AI systems
Production-grade AI systems, not prototypes. Every delivery is async, monitored, and documented.
Turn your company's documents, databases, and knowledge base into an always-on AI that answers with precision and cites its sources.
Multi-step AI agents that reason, use tools, call APIs, and complete complex tasks autonomously — with built-in guardrails and logging.
Connect your SaaS stack and eliminate manual work. AI-triggered workflows across CRMs, communication tools, and internal databases.
Deploy streaming chatbots with deep product knowledge, escalation logic, and real-time observability. Handles 80%+ of queries without human touch.
Full-stack monitoring for your AI systems. Track token usage, response quality, latency, and eval scores — then optimize systematically.
End-to-end AI product builds from backend API to polished UI. Scalable, containerized, and production-deployed on your cloud of choice.
Real projects. Real results. Each one production-deployed with full monitoring.
RAG system for a litigation firm. Indexes 10,000+ legal documents with semantic search, clause extraction, and citation tracing. Associates find answers in seconds instead of hours.
Multi-agent LangGraph system that autonomously researches prospects, enriches CRM records, personalizes outreach, and tracks replies — replacing 3 hours of daily SDR work.
AI chatbot for a clinic chain that handles appointment booking, symptom triage, and escalation routing — with HIPAA-aware guardrails and an integrated observability dashboard.
Real results from real teams — not cherry-picked demos.
"Our support ticket volume dropped 62% in the first month. The AI agent Quantum Leap built handles nuanced clinical questions better than I expected any chatbot could."
"They delivered a production-grade RAG pipeline in 4 weeks. Our legal analysts now draft briefs 3× faster. The quality of the retrieval blew every competing solution out of the water."
"Quantum Leap integrated IoT anomaly detection directly into our fleet management dashboard. Predictive maintenance savings paid for the project in 6 weeks flat."
We use the best AI infrastructure available — not the most hyped. Our stack is chosen for reliability, observability, and scale.
A proven process that prioritizes working software over long planning cycles.
We map your workflows, identify the highest-impact automation opportunity, and define success metrics together.
30-min callA working proof-of-concept in 1–2 weeks. Real data, real API calls — not mockups. You evaluate before we scale.
1 – 2 weeksProduction deployment with async architecture, Docker containers, CI/CD pipelines, and full LangFuse monitoring from day one.
LangFuse monitoringContinuous improvement via eval suites and real-world feedback. We track quality metrics and iterate on prompts, retrieval, and logic.
OngoingNever. We integrate AI at the API and service layer — your existing stack stays intact. Whether you're on Django, Rails, Node, or .NET, we bolt in AI capabilities without a rewrite. Our typical integration touches 2–4 new service files, not hundreds.
A focused MVP — say a document Q&A agent or a lead qualification bot — ships in 3–5 weeks. More complex systems with fine-tuning, multi-agent orchestration, or heavy data pipelines run 8–14 weeks. We give you a fixed-scope estimate before any code is written.
Whichever fits your use case and budget. We're model-agnostic — we've shipped with GPT-4o, Claude 3.5, Gemini 1.5, Mistral, and open-source models like Llama 3. For privacy-sensitive workloads we can run entirely on-prem with no data leaving your infrastructure.
You do — 100%. Every line of code, every fine-tuned model weight, every prompt template is transferred to you at project close with full documentation. No lock-in, no licensing fees, no "platform" you have to keep paying for.
We maintain a 4-hour overlap with US Eastern (9 AM–1 PM EST) and an 8-hour overlap with Central European Time — enough for a daily standup and async review cycles. Most clients say timezone friction is a non-issue within the first week.
Yes. We deploy to your cloud (AWS, GCP, Azure, or Vercel/Railway) and wire up observability with LangSmith or custom logging so you can see every LLM call, latency, and cost in a dashboard. We also offer a 60-day post-launch support window.
Tell us what you're building. We'll respond within 24 hours with a concrete approach — even if we don't end up working together.
We'll be in touch within 24 hours.