Why SolvxAI
Pulse AI. The intelligence inside the operating system.
The layer that plans the work, runs the analysis, convenes the disciplines, and remembers every decision — governed, auditable, and yours.
The agentic core
Plan. Perform. Reconcile. Decide.
A chatbot answers a question. An agentic system does the job — the difference between asking for directions and having a colleague who drives.
Plans the approach
Given an objective, it lays out the work and shows it to you.
Does the engineering
It runs the analysis on live data with real engineering tools.
Reconciles the disciplines
It merges specialist findings into one attributed answer.
Brings it to you
It pauses for the judgment calls and builds the deliverable.
The brainstorm
A brainstorm session with your own cross-discipline engineering team.
Bring a question where disciplines collide — spacing, a bid, an underperforming pad — and the system recognizes which professions' assumptions interact, then convenes them. Each seat is a specialist with its own mandate, its own access to your data, and its own professional standards. They join the discussion by name — and you can address any of them directly.
Land & A&D Analyst
Reservoir Engineer
Drilling Engineer
Economics colleague — can you test that capital framing?
Question for you
Your inputRecommendation — agreed 4/4 · 2 decisions for you
Convene
It reads the question, not just the words.
The system identifies where informed professionals could reasonably disagree — where one discipline's conclusion changes another's inputs — and invites the specialists whose expertise actually interacts: a reservoir engineer, a geomechanics analyst, a completion engineer, an economics analyst. Each arrives with a distinct mandate to test, not to agree.
Explore
Every opinion starts in your data.
Before a panelist may weigh in, it explores the evidence itself — the logs, the production history, the lease file. Each specialist investigates independently, so the panel doesn't group-think its way to the first plausible answer.
Challenge
Cross-examination is the point.
Panelists question each other — and a question demands an answer before the discussion can conclude. They separate evidence from assumption, challenge both, and put questions to you when only you can resolve them. The debate is the quality control.
Converge
Agreement earned, never faked.
The panel closes on what it agrees on, what it still disputes, and the smallest set of decisions only you can make. Disagreement is surfaced, never papered over — and the conclusion flows straight into a plan awaiting your approval.
This isn't a prompt. It's a governed discussion among independent professionals, on your data, with you at the table.
The conductor
It knows the order the oilfield works in.
Every discipline's output is another discipline's input. SolvxAI carries that map.
A raw-log question walks itself all the way to booked volumes.
The frac design asks for fluid efficiency — and knows exactly which test produces it.
The lift design serves the operating point; the operating point needs the fluids first.
The well plan inherits the rock's reality, not an assumption about it.
What it does
- Resolves each dependency the cheapest correct way — reusing what you already have before recomputing anything
- Routes each unit of work to the specialist that owns it, at the right moment
- Fans independent work out in parallel and runs dependent work as a relay — twenty wells take as long as one
- Reconciles contradictions with stated reasoning — it never silently averages two disagreeing picks
- Asks the one question that changes the answer before it starts — not after the report is wrong
One question in. The right specialists, in the right order, on your data — one attributed answer out.
Cadence
A team member who works the night shift.
Put the system on a schedule — from every fifteen minutes to every week — and it stands watch so your engineers don't have to.
Production watch
It walks the field on schedule: compares every well's actual rate against its fitted decline, re-reads the rate-transient behavior when something drifts, and separates noise from a genuine problem — liquid loading, a pressure anomaly, an unexplained falloff. The moment a well crosses the line, the designated engineers have an email with the evidence attached.
New-well intake
New wells landing in the workspace are picked up automatically — data checked, baselines fitted, diagnostics run — so the portfolio never quietly grows stale.
The recurring report
Weekly variance, monthly roll-ups, the Monday-morning report — produced on schedule, every number attributed, delivered to the right inbox.
You set the cadence and the recipients. It does the nights and weekends.
The compounding advantage
Most software depreciates.
SolvxAI appreciates.
A conventional tool knows no more about your fields in year three than it did in year one. SolvxAI gets more valuable every quarter — a proprietary asset built as a by-product of the work your team already does.
The engine
The Reservoir Decision Memory
The core IP that makes the platform appreciate — not a copy of your files, but a living model of your fields and the decisions made on them.
Where the knowledge lives
It maps every file you upload, every analysis run in the workspace, and every conversation with the agent — so nothing is lost between sessions or people.
An oil & gas ontology
It sits on a model of your fields — asset, well, reservoir, formation — so information is organized the way an engineer thinks, not the way files happen to be named.
The decisions, captured
Every key decision and conclusion reached collaborating with the AI is retained and attributed — the judgment, not just the data.
An institutional asset no competitor can buy — because no competitor has your data and your decisions.
The gap
Where general-purpose AI stops.
Physics decides the number.
Every figure comes from deterministic, SPE-cited engineering functions — not token prediction. Same inputs, same answer, every time.
A panel, not a persona.
Independent specialists that explore, reason, and cross-examine — not one model asked to imagine a debate.
The whole lifecycle, one thread.
From the wireline log to the deal table — the analysis you ran in April informs the bid you make in November.
Memory that compounds.
Every study grows a decision memory on an ontology built for oil & gas — yours to download, query, and build on.
Provenance an auditor accepts.
Every number traces to a source file, a method, and a citation.
A data boundary you control.
Its own isolated instance — never your machines, file systems, or terminals — and you can host the entire thing yourself.
Capability with control
For an enterprise, capability without control is a liability.
The boundary between “the AI wants to” and “it actually happened” is always a human one.
The AI proposes; a person decides
Anything irreversible — changing system-of-record data, sending a communication — pauses for explicit human approval.
Every action, logged and reviewable
Every AI action and every change to a shared file is recorded — who, when, what — as a complete, reviewable trail.
Inside its own governed boundary
Organization, workspace, and project are hard walls. One team — or one client — never sees another's data.
Control is a dial, not a surprise
Administrators govern who can use it, what it can reach, the spend, and which AI models are permitted.
Your data, your boundary
Subsurface data is among the most sensitive assets you own. It is treated that way.
Runs in its own isolated space
It operates inside its own secured environment — never on your machines or your network drives.
No permanent links
Files are never served from permanent URLs — every access is authenticated and short-lived, checked on each fetch.
Granted, checked, revocable
The AI reads a file only where a folder was deliberately granted to a project — and revoking access cuts it immediately.
Why now
The capability arrived as the need became urgent.
Agentic AI has matured
The capability to plan, perform, and reconcile real work — not just answer questions — has arrived.
The knowledge cliff is here
Roughly 2.4 senior workers near retirement for every entrant under 25, and 3–8 years to rebuild a competent petroleum professional. The understanding is walking out the door.
Always the best AI. Never locked in.
Independent of any single AI provider — it uses the best available model and switches seamlessly as better ones arrive. The intelligence under the hood upgrades; the asset you build on top of it does not move.
On purpose
Generic tools treat oil & gas as text. SolvxAI treats it as physics.
Unit-safe by construction
The silent unit-conversion error — the classic way spreadsheets lie — is designed out. Every value carries its units and basis.
Conventions stated, always
Percentile conventions, validity bands, and method citations travel with every result.
Uncertainty rides along
Every parameter says whether it is well-determined or weakly constrained — so you know which numbers are load-bearing.
Honest about its altitude
Planning-grade output that says plainly where a qualified evaluator still signs.