AI-Powered Automation in San Francisco, United States

Yes. We deliver AI-Powered Automation to businesses across San Francisco and United States. Our team operates remotely-first via GoHighLevel and Slack, so geography is never a blocker. We've served 500+ businesses across 40+ countries.

Most San Francisco-area clients are operational within 7-14 days. Measurable revenue impact (recovered missed calls, faster lead response, automated follow-ups) typically shows up within the first 30 days.

AI-Powered Automation comes with three plans: Founder Freedom ($997/mo), Famous Founder ($2,997/mo — most popular for San Francisco SMBs), or Empire Builder ($4,999/mo for agencies). Build fee covers custom configuration, integrations, and team training.

Two reasons. (1) Cost: an SF AI engineer is USD 250-380K total comp. We deliver production engineering (evals, monitoring, retrieval) for a fraction of that on fixed-price. (2) Velocity: we have shipped a large library of production AI systems. Pattern library that internal teams take 12-18 months to build.

No - different model. We are an agency delivering production engineering services, not a product company hiring researchers. Most of our work is implementation of well-understood patterns (RAG, agents, voice) into client-specific contexts.

Specific things: (1) Eval suite with 100+ test cases per agent, run on every prompt change. (2) Cost monitoring per request, alerts on anomalies. (3) Latency monitoring with p50/p95/p99 budgets. (4) Retrieval quality metrics tracked separately. (5) Rollback procedures for prompt updates. Most AI agency deliverables ship without any of these and break silently.

Yes - augmentation is one of our most common SF engagement shapes. Your internal team focuses on differentiated product work; we handle the production engineering layer (evals, observability, retrieval, integrations) that internal teams perpetually deprioritize.

It depends on the application. AI chatbots and workflow automations work well from day one with a good knowledge base, not requiring historical data. Predictive models (like lead scoring) benefit from 3-6 months of historical data to train on. We'll advise you on what's immediately actionable versus what requires more data accumulation first.

We build AI systems with guardrails, the AI is trained on your specific knowledge base (FAQs, product info, pricing, policies) and is constrained to only answer questions within its training scope. For questions outside its knowledge, it escalates to a human rather than hallucinating an answer. You review and approve the knowledge base before go-live.