AI Agent Development Company in San Antonio

Ranges, not a single number, because scope drives everything. A scoped agent proof of concept covering one agent, three to five tools, an evaluation suite, an action-log view and a hosted demo behind SSO typically runs USD 30,000 to 70,000 over six to ten weeks. A custom production agent, meaning something like claims-triage drafting for a carrier, SOC alert triage wired into your SIEM, or engineering-documentation assistance inside a CUI enclave, typically runs USD 110,000 to 320,000 including guardrails, the human-in-the-loop console, observability and the compliance documentation pack. A multi-agent platform with role-specialized agents, shared memory, custom evaluators and integration into core systems such as Guidewire, ServiceNow, SAP or an MES runs USD 300,000 to 800,000 and up as a phased program. San Antonio senior engineering rates run meaningfully below San Francisco and New York, generally 30 to 45 percent lower at equivalent seniority, and below Austin as well because Tesla, Oracle and Samsung bid up that market. Work inside a CUI or classified-adjacent boundary costs more, usually 20 to 30 percent, because the hosting, access control and evidence burden are all heavier. We quote fixed fee against a signed statement of work.

Yes, and in San Antonio that is the common case rather than the exception. The governing constraint is that CUI stays inside the boundary your System Security Plan already describes. In practice that means the agent, its retrieval index, its logs and its model inference all sit inside Azure Government or AWS GovCloud at FedRAMP Moderate or High, or inside your own on-premise enclave, with no calls out to commercial model endpoints. For work where even a government cloud is off the table we run self-hosted open-weight models on private GPU capacity. Access follows your existing personnel controls, which is the honest limit on our offshore model: our Chandigarh engineers work the non-CUI layers such as orchestration scaffolding, evaluation suites and front-end work behind clean interfaces, while anything touching marked data stays with cleared or US-person staff on your side of the boundary and our Edmonton leads coordinate. The 48 CFR CMMC acquisition rule took effect November 10 2025 and phases in over three years, so new awards and option years increasingly carry the clause. We build to the controls your assessor expects and we produce artifacts that map to NIST SP 800-171 practices, but we are not your C3PAO and we say so plainly.

The Texas Responsible Artificial Intelligence Governance Act was signed as HB 149 on June 22 2025 and took effect January 1 2026. It is narrower than the sweeping draft it grew from. The core of the statute is a set of intent-based prohibitions that apply to everyone: developing or deploying an AI system with the intent to incite or encourage self-harm, harm to another person or criminal activity, with the intent to unlawfully discriminate against a protected class, or to produce child sexual abuse material or unlawful deepfake sexual material. A second set binds governmental entities specifically, covering social scoring and biometric identification from publicly available data without consent. It adds disclosure duties when a government agency interacts with a consumer through AI, sets up a regulatory sandbox and a Texas AI Council, and gives the Attorney General exclusive enforcement with a written notice and a cure period before penalties attach. The provision that matters most to a buyer is the safe harbor: aligning with the NIST AI Risk Management Framework is a recognized defense. So our discovery includes an explicit prohibited-use intent screening, and every build ships a NIST AI RMF aligned risk profile plus evaluation records, so if a notice ever arrives you hand over a folder instead of starting an archaeology project.

TDI issued Commissioner's Bulletin B-0003-26 on June 12 2026, addressed to all regulated entities and titled simply Use of artificial intelligence. It points to the NAIC Principles on Artificial Intelligence adopted in 2020 as an appropriate guide and sits alongside the state's own AI code of ethics. The practical content is short and it still changes architecture. Any decision affecting a consumer that is made or supported by AI has to comply with existing Texas insurance law, including unfair trade practice and unfair claims settlement standards. TDI expects regulated entities to maintain robust governance, risk-management controls and internal audit functions, and it monitors AI use through examinations and product filings while investigating consumer complaints. The bulletin encourages verification and testing methods that identify errors and bias, and it applies to any third party working with a regulated entity, which includes us. Most importantly, if a regulated entity uses AI to make a consequential decision, TDI expects a person to review and agree with the decision before action is taken. So the agents we build for this market draft, summarize, cite and route. They do not deny, rescind, price or close. The human sits on the gate and the log records who approved what and when.

Every state-changing action ships behind an explicit approval gate by default, and we relax that only when a documented risk review supports it. We sort every tool the agent can call into four tiers. Read-only calls carry no gate. Low-risk writes get post-hoc review and an optional pre-call gate. High-risk writes need a mandatory pre-call gate with a single named approver. High-impact actions need a mandatory pre-call gate with two approvers. In San Antonio deployments the high-impact tier reliably includes any adverse insurance determination, any write into a claims or policy system of record, any customer-facing communication, any financial transaction, any clinical order, any change to a utility work order that dispatches a crew, and any release of data across a CUI boundary. Approvers see a structured payload showing the agent's intent, the supporting evidence with citations, the predicted impact and the policy the action must satisfy, with one-click approve or reject. The action log captures approver identity, timestamp, the full context the agent had, and the outcome. That log is the artifact your internal audit, a TDI examiner, or a CMMC assessor will actually ask to see, so we design it for them rather than as an afterthought.

We say this plainly because it matters for planning: Codazz has no San Antonio office. We are headquartered in Edmonton, Canada with a second engineering center in Chandigarh, India, and we have delivered more than 500 projects since 2018 with over 200 engineers. For a San Antonio client the practical arrangement is that Edmonton runs on Mountain Time, exactly one hour behind Central, which is the easiest offset in remote software delivery. Your 9 AM CT standup is 8 AM for us, a 2 PM CT demo is 1 PM, and there is no day where a question sits unanswered because the team already went home. Chandigarh picks up the overnight window, so work moves while San Antonio sleeps and the Thursday demo has real progress in it. What remote delivery does not solve is physical presence inside a controlled facility. If your program requires on-site access to a SCIF, a plant floor or a secure lab, that portion stays with your staff or an on-site partner and we architect the interface so the remote team never needs to cross that line. Everything else, including discovery workshops, design reviews, red-team readouts and go-live support, runs on video with your calendar. Reach us at +1 (403) 604-8692.