Contact UsContact UsPrevent production losses and safety risks with RISHI. Turn complex upstream data into actionable guidance for early, confident, and unified team action.
Book a Consultation CallUpstream and midstream operations face unique geographical and physical challenges. Assets are often remote, distributed over hundreds of miles, and subject to highly transient conditions. A single unexpected surge, slugging event, or hydrate formation can shut down production, trigger emergency flaring, or damage critical infrastructure like compressors and pipelines within minutes.
While SCADA systems and field sensors generate massive volumes of industrial data, insight into the "why" behind an alarm is often missing, and critical troubleshooting frequently requires mobilizing specialized SMEs to remote sites, causing costly delays. Teams are forced to act fast with incomplete information, knowing every decision affects safety, environmental compliance, and the stability of the entire gathering network.
RISHI shifts the operational culture from intuition to evidence using Industrial AI:
In traditional operations, teams react to a single symptom like rising casing pressure or pipeline pressure loss. RISHI evaluates the full production system simultaneously, correlating pressures, rates, temperatures, and equipment health. The Benefit: Instead of reacting to isolated alarms, teams see the multi-variable pattern that explains why production is changing.
RISHI drives value through speed, consistency, and margin protection using decision intelligence.
Reduces Mean Time to Diagnose (MTTD) from a typical 4-6 hour window to under 2 hours.
Validated recommendations allow teams to stabilize units faster, reducing Mean Time to Recover (MTTR).
By converting noise into contextual "Fault Scenarios," RISHI reduces operator cognitive load during high-risk events.
Avoidance of just one unplanned slowdown per quarter can save $0.5M – $1.5M annually.
Maximizing Asset Uptime and Flow Assurance Through Intelligent, Real-Time Operational Decision Support
Answers to common questions about how RISHI supports refining and petrochemical excellence.
Traditional systems are excellent at monitoring but limited in diagnosis. RISHI adds an intelligence layer that explains why deviations occur and recommends validated actions using Fault-Tree logic, engineering principles, and machine learning.
Yes. RISHI is designed for real-time decision support, correlating multi-asset data instantly to guide operators and engineers during high-pressure situations, even when experts are not immediately available.
No. RISHI acts as a force multiplier. It automates data analysis and captures expert knowledge, allowing engineers to focus on higher-value decisions while ensuring their logic is available across every shift.
RISHI creates a centralised Case Library that records symptoms, root causes, and successful actions, ensuring lessons learned are applied consistently across assets and time.
RISHI is fully explainable. Every recommendation is traceable through transparent Fault-Tree logic and engineering reasoning, allowing teams to review and trust the guidance before acting.
Oil and gas operations typically see measurable impact within months, including faster diagnosis, reduced production losses, and avoided integrity events. Preventing even a single prolonged production upset or pipeline restriction can deliver significant, rapid payback.
See how RISHI helps teams detect issues early, diagnose faster, and make confident operational decisions. It turns complex process behavior into clear, actionable guidance to resolve unit upsets and slow degradation.
View BrochureNo form submission required
