AI Agent Development Company in San Diego

Honest ranges, because scope drives the number far more than geography does. A scoped agent proof of concept covering one agent, three to five tools, an evaluation suite, an action-log dashboard, and a hosted demo behind SSO typically runs USD 35,000 to 75,000 over six to ten weeks. A custom production agent, meaning something like prior-authorization drafting for a health system, regulatory-document assembly for a biotech, or maintenance-record triage for a defense sustainment program, typically runs USD 110,000 to 300,000 including guardrails, the human-in-the-loop console, observability, and the compliance documentation pack. An enterprise multi-agent platform with role-specialized agents, shared memory, custom evaluators, and integration into Epic, SAP, Veeva, or a defense logistics system is a multi-phase program at USD 300,000 to 800,000 and up. San Diego senior engineering rates sit meaningfully below San Francisco and New York, though the Qualcomm and defense-primes talent pool keeps them above most inland US metros. Work inside a CMMC or ITAR boundary carries a real premium because accredited environments, US-person staffing constraints, and documentation overhead all add engineering time. We quote fixed fee against a signed statement of work.

Yes. California has the most developed state privacy regime in the country. The California Consumer Privacy Act was signed as AB 375 on June 28 2018 and took effect January 1 2020, then was substantially amended by the California Privacy Rights Act, passed as Proposition 24 on November 3 2020 and fully operative January 1 2023, with enforcement from July 1 2023. Unlike most states, California created a dedicated regulator, the California Privacy Protection Agency, which has independent rulemaking and enforcement power alongside the Attorney General. For an agent build the practical consequences are concrete. Rights to know, delete, correct, and opt out of sale or sharing follow the data into agent memory, retrieval indexes, and logs, so we build deletion propagation across the vector store, conversation history, and analytics pipeline rather than just the primary database. Purpose limitation means your notice has to actually describe that personal information flows into an agent. SB 1223, signed September 28 2024, added neural data to the sensitive personal information category, which matters for any San Diego neurotech or wearable buyer. We ship a per-tool data map and a deletion-propagation test in the QA suite.

The CPPA finalized regulations on automated decisionmaking technology, risk assessments, and cybersecurity audits, approved by the Office of Administrative Law in September 2025 and effective January 1 2026. The operative deadline is section 7200: a business that uses ADMT for a significant decision before January 1 2027 must be in compliance with the whole ADMT article no later than January 1 2027, and a business that starts after that date must be compliant whenever it is using ADMT for a significant decision. Everything in that article rides on the same deadline, including the pre-use notice, the opt-out, and the consumer's right to access information about the ADMT. Risk assessments are on a separate clock: for processing a business initiated before the regulations took effect and continued afterward, the assessment must be completed no later than December 31 2027, and for assessments conducted in 2026 and 2027 the submission to the Agency is due no later than April 1 2028. A significant decision covers the provision or denial of financial or lending services, housing, education enrollment or opportunity, employment or independent contracting, and healthcare services. That sweeps in more San Diego agent use cases than buyers expect: a prior-authorization agent at a health system, a credit or underwriting assistant, an applicant-screening agent. Our discovery includes an ADMT scoping memo that either documents why the agent falls outside the definition or builds in pre-use notice, opt-out routing to a human path, access-request handling, and an appeal channel.

We build to the architecture your facility security officer and export-compliance lead sign off on, and we say plainly that we are not your export-control counsel. The governing rules are real and dated. The CMMC program rule at 32 CFR Part 170 has been in effect since December 2024, and the acquisition rule at 48 CFR was published September 10 2025, with the DFARS 252.204-7021 clause appearing in DoD solicitations from November 10 2025. Phase 1 runs a year on self-assessment, with Phase 2 certification requirements beginning November 10 2026. ITAR at 22 CFR Parts 120 to 130 and EAR at 15 CFR Parts 730 to 774 govern technical data. Architecturally that means inference stays inside AWS GovCloud US-West, Azure Government, or an on-premise enclave, model weights are self-hosted rather than called through a commercial frontier API, and export-controlled documents live in a segregated retrieval index the general agent population cannot reach. Access to the agent and its logs follows US-person constraints where a program requires them, which means our Edmonton and Chandigarh engineers work on non-controlled layers such as orchestration scaffolding, evaluation suites, and UX behind clean interfaces, with controlled data never leaving the accredited perimeter.

AB 316 was signed on October 13 2025 and it is short, blunt, and directly relevant to anyone shipping an agent. It bars a defendant who developed, modified, or used an artificial intelligence system from asserting as a defense that the AI autonomously caused harm to the plaintiff. It does not remove other affirmative defenses or change causation and foreseeability analysis, but it closes the argument that the model went off on its own and nobody is responsible. In practice this raises the value of two things we already build. The first is a complete action log: every tool invocation, the inputs, the policy that authorized it, the human who approved it if a gate applied, and the outcome, stored immutably. If your counsel has to reconstruct what the agent did eighteen months later, that log is the record. The second is designed accountability at the gate. Because you cannot disclaim the agent, every state-changing action ships behind a named human approver by default, and relaxing that posture requires a documented risk review rather than a preference. AB 316 is a good reason to resist autonomous write access, not a compliance checkbox.

Clinical workflow agents at San Diego health systems ship inside a tight perimeter. PHI stays in US-region infrastructure under a signed business associate agreement, minimum-necessary scoping limits what reaches a model context, no PHI goes to model training, and every inference is logged for audit. California adds two layers on top of HIPAA. AB 3030, effective January 1 2025, requires that generative AI output used in written or verbal patient communications about clinical information carries a prominent disclaimer identifying it as AI-generated plus clear instructions for reaching a human provider, with an exemption where a licensed provider reads and reviews the communication before it goes out. We usually design for that exemption, because a clinician-reviewed message is better product and better medicine. SB 1120, the Physicians Make Decisions Act, also effective January 1 2025, means a licensed physician must make medical-necessity determinations in utilization review, so an agent can assemble evidence, draft an appeal, and surface policy citations, but it cannot deny, delay, or modify care. The California Confidentiality of Medical Information Act applies alongside HIPAA and is stricter in places, so we scope disclosure controls to CMIA rather than assuming HIPAA is the ceiling.