One of many midstream use cases. This example focuses on ILI data analysis and dig program optimization, the core of pipeline integrity management where Lumina was first proven.
You have terabytes of in-line inspection data, and your senior engineers already know how to read it. Today a single decision often waits on a data engineer to write the SQL query, and that handoff adds both delay and risk.
CEPA and PHMSA expect traceable, verifiable records behind each integrity decision, so the manual path through spreadsheets, interaction rules, burst-pressure math, and dig programs takes real time to complete. The encouraging part is that the judgment already lives inside your team, and the opportunity is to give that judgment the reach to cover the whole system at the speed the data now arrives.
Traditional approaches were not built for the scale and complexity of modern operations.
Engineers manually sift through millions of rows, applying interaction rules and calculating burst pressures in spreadsheets, so a single run takes weeks.
Growth rates are calculated linearly between runs. They don't account for coating condition, CP readings, or soil chemistry.
CER/PHMSA require auditable decision trails, yet most integrity decisions are documented in emails and meeting notes.
Without cost-benefit analysis across all anomalies, dig programs over-excavate low-risk features and miss high-risk interactions.
Three layers of intelligence working together: reasoning agents, proactive detection, and multi-agent deliberation.
Lumina agents ingest ILI data, apply CEPA/ASME interaction rules, calculate burst pressures (B31G, Modified B31G, RSTRENG), and classify defects, all as verifiable SQL.
Every calculation is SQL you can verify. No black box.
Analyzing Run_2024_Segment_4.csv (2,405,100 sensor rows)... Validated against ASME B31G Applied CEPA Interaction Rules Critical Finding: Cluster Interaction at MP 102.4 Two defects (Depth 35% & 42%) within 15mm axially → Effective Failure Pressure: 850 PSI (Below MOP) → Immediate dig required
ALERT: Corrosion growth rate acceleration detected at MP 98-105 3 consecutive runs show exponential growth pattern (R²=0.94) Correlation: CP readings in this segment show 15% potential drop over 18 months Soil resistivity: 800 Ω·cm (highly corrosive) → Recommend: Prioritize CP rectifier assessment + coating condition survey
The Radar scans across ILI runs, CP surveys, and coating assessments to detect patterns: corrosion clustering, growth rate acceleration, and coating-soil interactions that indicate emerging risk.
The Radar surfaces issues the operator didn't know to look for. Before they become incidents.
Integrity, operations, and compliance agents deliberate on dig program priorities. Each weighs safety, cost, and regulatory requirements from their domain perspective.
The output is grounded in facts (SQL results), not hallucination. Every recommendation carries a full audit trail.
Integrity Agent: 47 features require assessment. 12 are critical (below 1.25 safety factor). Operations Agent: Segment 4 has a 30-day outage window in Q3. Segment 7 is continuous-flow. Compliance Agent: CER Condition 6 requires all critical features addressed within 180 days. → Consensus: Bundle Segment 4 critical digs (8 features) into Q3 outage. Segment 7 features (4) require hot-tap or clamp repairs.
Lumina addresses the four strategic problems that hold operators back.
Analyze entire ILI runs in minutes, not weeks. One engineer can manage the integrity program for an entire pipeline system.
Optimize dig programs with cost-benefit analysis, reducing unnecessary excavations by 30-50% while improving safety outcomes.
Interaction rules, corrosion models, and integrity playbooks are encoded in the system, not in the Senior Engineer's retirement plan.
Every burst pressure calculation, interaction rule application, and defect classification is backed by SQL you can verify and audit for CER/PHMSA.
Specialized AI agents that power this workflow.
Integrity Engineer
Specializes in ILI analysis, corrosion growth rates, burst pressure calculations, interaction rules, and dig program optimization grounded in CEPA/ASME standards.
Energy Optimizer
Monitors pump station energy against grid pricing. Optimizes compressor scheduling for cost and carbon intensity.
Data Scientist
Handles ILI data ingestion, vendor format normalization, fuzzy matching across runs, and unit conversion.
This is just one of many use cases
Pipeline integrity & safety is one example of how Lumina reasons on operational data. Across Oil & Gas, every domain has use cases where AI agents can add value.
Not ready to commit? Stay up to date as we release new capabilities and industry-specific agents.
View all Oil & Gas use cases