AI Consulting in Los Angeles

The short answer is: data never leaves the perimeter you define, and we scope access narrowly before any build begins. For production companies, that means integrations connect only to the specific project folders, budget sheets, and scheduling tools the build needs to read — not a blanket connection to the studio's full file system. Contract documents that move through any automated workflow are processed using enterprise AI endpoints with zero-retention, no-training contractual terms, meaning the content of a deal memo or talent agreement isn't stored or used for model training after the request completes. We document every data flow before credentials are exchanged, and the executive producer or head of business affairs signs off on scope. If the production is running inside a studio's own infrastructure, we can deploy the integration layer inside that environment so documents stay behind the studio firewall entirely.

Yes, and it's one of the more common builds for LA-based agencies. The typical shape: a structured layer on top of whatever CRM the agency already uses — often HubSpot, Salesforce, or a legacy custom system — that surfaces relationship-health signals automatically. Which clients haven't had a meaningful touchpoint in the last thirty days. Which open deals have gone quiet. Which upcoming renewal conversations need to be initiated before a competitor gets there first. The build can also handle inbound inquiry routing — submissions, casting requests, partnership inquiries — so agents are responding to prioritized, pre-screened items instead of a raw inbox. We scope these builds to the agency's actual workflow rather than forcing a platform change. If the existing CRM is functional and the team knows it, we augment it rather than replace it.

That's exactly the kind of build we do. Shopify and Klaviyo both have well-documented APIs, and most of the high-value automation for DTC brands lives in the gap between those two systems — customer behavior signals in Shopify that should trigger smarter segmentation and timing in Klaviyo, support ticket patterns that should feed back into product decisions, repeat-purchase data that should surface to the merchandising team before they run a campaign. We build the connective tissue, not a new platform. On the customer service side, an AI triage layer can handle the high-volume, low-complexity tickets — order status, return initiation, size guidance — and route the exceptions that actually need a human. Most DTC brands with a support team of two to four people see meaningful time savings within the first few weeks, with the human team shifted toward the conversations that drive retention rather than the ones that are just lookup tasks.

It's viable, but the architecture has to be designed around the compliance constraint from the start — not retrofitted. For ITAR-covered workflows, that means keeping all data processing within US-person-accessible infrastructure, using AI models deployed in compliant cloud environments (Azure Government, AWS GovCloud, or on-premises deployment), and ensuring that no technical data routes through endpoints that could expose it to non-US persons in the model serving chain. The business development workflows that benefit most — contract tracking, proposal coordination, subcontractor document management, BD pipeline follow-up — can be automated within those constraints. We scope the compliance architecture before writing a single line of integration code, and the documentation we produce is written to support your export control officer's review. The audit is usually the right starting point because it maps which workflows involve controlled technical data and which don't, so you're not applying ITAR-level controls to parts of the operation that don't require them.

The $99 AI readiness audit takes about a week end-to-end — you fill out an intake form, we review your current tools and workflows, and you get a written report identifying the highest-leverage automation candidates with an honest assessment of complexity and risk. If one workflow is clearly the right first build, we scope and price it after the audit. Fixed-price builds for a single well-scoped capability typically run two to four weeks from signed agreement to go-live, depending on how many third-party integrations are involved and how quickly your team can turn around access provisioning and review cycles. If you're not sure which workflow to tackle first and want to talk through the options before committing to a build, the $497 Founder Review Call gets you ninety minutes with the founder — no junior consultants — and a written prioritization memo you can use internally. Most LA-based operators who've been burned by slow enterprise software implementations are surprised that a real working system can ship in under a month.