AI Agent Developer: Houston

Hire an AI agent developer in Houston.

Shell, ExxonMobil, ConocoPhillips, and Halliburton operate large facility footprints that require regular documented inspections. Field engineers currently spend 40 percent of their time on documentation: pulling the inspection schedule, finding the right procedure, generating checklists, and writing up reports. An AI agent handles the documentation steps so the engineer does the inspection.

Houston Medical Center hospitals face a different problem. Prior authorization currently takes 3 to 5 days at most Houston health systems. A prior auth agent that pulls clinical records, matches against payer criteria, and drafts the authorization request reduces that to same-day submission on straightforward cases.

We build agents for both. Fixed scope, fixed price, you own the code.

How we work

Tell us about your field operations or clinical workflow.

The inspection documentation problem.

An ExxonMobil field engineer earning $110,000 to $130,000 per year spends roughly 40 percent of their work hours on documentation: pulling inspection schedules, locating the applicable procedure from a library of hundreds, generating a pre-inspection checklist, and drafting the post-inspection report. That is approximately $50,000 per engineer per year in documentation labor.

The documentation work is structured and repeatable. The inspection schedule is in a database. The procedures are in a document management system. The checklist items are in the procedure. The report template is standardized. None of these steps require engineering judgment. An agent executes them.

A 10-person field team costs $1.1 million to $1.3 million annually in salary. If 40 percent of that time is documentation, the team is spending $440,000 to $520,000 per year on work that could be automated. An agent system that handles inspection scheduling, checklist generation, and report drafting for a 10-person team pays for itself within weeks.

Break-even comes fast at that ratio. The recurring cost is API fees, which typically run $300 to $600 per month for a team of that size.

What changes with an operations agent.

Specific changes to the field engineer's workday.

Inspection prep takes 5 minutes instead of 45

The agent retrieves the equipment record, identifies the applicable procedure, and generates the pre-inspection checklist. The engineer arrives with a printed or digital checklist already prepared.

Report drafts start populated

After the inspection, the engineer inputs findings. The agent drafts the full inspection report using a template populated with equipment data, procedure reference, and the engineer's inputs. The engineer reviews and signs.

Scheduling conflicts surface automatically

The agent monitors the inspection schedule and flags when an inspection is at risk of being missed due to resource conflicts or equipment downtime. The planner sees the conflict before it becomes a compliance issue.

Healthcare: prior authorization agents.

Prior auth at most Houston health systems takes 3 to 5 days. Most of that time is documentation assembly and submission, not clinical review.

Clinical record retrieval

The agent pulls relevant clinical records from the EHR, Epic or Cerner, and structures them for the auth request. The clinical staff member no longer assembles the record package manually.

Payer criteria matching

The agent compares the clinical data against the payer's published coverage criteria for the requested procedure. Criteria are maintained as a structured database your team updates when payers change requirements.

Authorization request drafting

The agent generates a complete prior auth request with supporting documentation attached. For Aetna, UnitedHealthcare, and Blue Cross Blue Shield of Texas, the format is specific. The agent produces it correctly.

Status tracking

After submission, the agent monitors auth status and flags payer responses that require follow-up. Denials include the denial reason extracted from the payer response, so the appeals team has the information ready.

Questions from Houston energy and healthcare teams.

How do you make sure an agent generates the correct pre-inspection checklist when there are multiple valid procedures for the same equipment type?: Equipment type is not sufficient on its own. The checklist selection logic uses a decision tree that factors in equipment type, service category, regulatory jurisdiction (API, OSHA, company-specific), and the inspection interval. Each combination maps to a specific procedure document. The agent retrieves the relevant procedure, extracts the checklist items, and presents them with the source procedure referenced. Your team can review and update the decision tree without code changes because it lives in a configuration file.
What happens when an agent encounters an inspection situation it has not been trained on, and how does it escalate?: The agent does not guess. When the equipment type, service category, or jurisdiction combination does not match any entry in the decision tree, the agent stops and flags the gap. The output is a structured escalation: which combination was not found, what the engineer needs to do to get a checklist, and a request to add the missing procedure to the system. No inspection moves forward on a blank checklist.
For prior authorization agents, how do you handle payers that require portal submission versus fax versus phone, since most agents cannot handle all three?: We scope the submission channel separately from the documentation assembly. The agent handles documentation assembly for all payers: pulling clinical records, matching criteria, and drafting the auth request. Submission channel is determined by a payer routing table your team maintains. For portal-capable payers, we build a web automation layer that handles portal submission. For fax-only payers, the agent generates a formatted fax-ready document and queues it for a staff member. Phone-only payers get an assembled document package the staff member reads from. The documentation work is the same regardless of channel.
What is the liability consideration when an AI agent is involved in generating safety-related documentation?: The agent generates drafts that a qualified engineer reviews and approves. The engineer's review is the authoritative act. We build the workflow so approval is an explicit step, not something that can be bypassed. The agent's output is logged, the engineer's review action is logged, and the final approved document carries the engineer's signature. This structure makes clear that the agent is a documentation tool, not a decision-maker. This matches how leading energy companies already use document automation tools in compliance workflows.

Walk us through your field operations or clinical workflow.

Describe what your engineers or clinical staff do manually today. We will reply within one business day with a scope and price range.

Hire an AI agent developer in Houston.

We build agents for both. Fixed scope, fixed price, you own the code.

The inspection documentation problem.

Break-even comes fast at that ratio. The recurring cost is API fees, which typically run $300 to $600 per month for a team of that size.

What changes with an operations agent.

Specific changes to the field engineer's workday.

Inspection prep takes 5 minutes instead of 45

The agent retrieves the equipment record, identifies the applicable procedure, and generates the pre-inspection checklist. The engineer arrives with a printed or digital checklist already prepared.

Report drafts start populated

Scheduling conflicts surface automatically

Healthcare: prior authorization agents.

Prior auth at most Houston health systems takes 3 to 5 days. Most of that time is documentation assembly and submission, not clinical review.

Clinical record retrieval

The agent pulls relevant clinical records from the EHR, Epic or Cerner, and structures them for the auth request. The clinical staff member no longer assembles the record package manually.

Payer criteria matching

Authorization request drafting

Status tracking

Questions from Houston energy and healthcare teams.

How do you make sure an agent generates the correct pre-inspection checklist when there are multiple valid procedures for the same equipment type?

Equipment type is not sufficient on its own. The checklist selection logic uses a decision tree that factors in equipment type, service category, regulatory jurisdiction (API, OSHA, company-specific), and the inspection interval. Each combination maps to a specific procedure document. The agent retrieves the relevant procedure, extracts the checklist items, and presents them with the source procedure referenced. Your team can review and update the decision tree without code changes because it lives in a configuration file.

What happens when an agent encounters an inspection situation it has not been trained on, and how does it escalate?

The agent does not guess. When the equipment type, service category, or jurisdiction combination does not match any entry in the decision tree, the agent stops and flags the gap. The output is a structured escalation: which combination was not found, what the engineer needs to do to get a checklist, and a request to add the missing procedure to the system. No inspection moves forward on a blank checklist.

For prior authorization agents, how do you handle payers that require portal submission versus fax versus phone, since most agents cannot handle all three?

We scope the submission channel separately from the documentation assembly. The agent handles documentation assembly for all payers: pulling clinical records, matching criteria, and drafting the auth request. Submission channel is determined by a payer routing table your team maintains. For portal-capable payers, we build a web automation layer that handles portal submission. For fax-only payers, the agent generates a formatted fax-ready document and queues it for a staff member. Phone-only payers get an assembled document package the staff member reads from. The documentation work is the same regardless of channel.

What is the liability consideration when an AI agent is involved in generating safety-related documentation?

The agent generates drafts that a qualified engineer reviews and approves. The engineer's review is the authoritative act. We build the workflow so approval is an explicit step, not something that can be bypassed. The agent's output is logged, the engineer's review action is logged, and the final approved document carries the engineer's signature. This structure makes clear that the agent is a documentation tool, not a decision-maker. This matches how leading energy companies already use document automation tools in compliance workflows.

Walk us through your field operations or clinical workflow.

Describe what your engineers or clinical staff do manually today. We will reply within one business day with a scope and price range.