Why SolvxAI
Pulse AI. The intelligence inside the operating system.
The layer that plans the work, runs the analysis, convenes the disciplines, and remembers what your team has learned — governed, auditable, and yours.
Watch the film: Real Engineering, Not Chatbots2:55 (opens in a new tab)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.
How the work runs
Five ways work runs.
Not every question needs a panel. The system gives the work the shape it actually has — from a single answer to a governed program of work.
Direct
One question, one specialist, answered in the conversation — no ceremony when none is needed.
Fanned out in parallel
Independent pieces go to specialists at the same time — each well, zone, or scenario on its own track — and come back together.
Relay chains
One discipline's output feeds the next, and each handoff is reconciled before the next leg starts — so an early mistake never travels silently downstream.
Governed workflows
Longer programs of work run as orchestrated workflows — with budgets you set, progress you can watch, and steering while they run.
Specialist panels
When disciplines collide, a panel convenes — each specialist explores, they challenge one another, and they converge on what is agreed and what is not.
The shape follows the question — and the result still comes back as one attributed answer.
Cadence
A team member who works the night shift.
Put the system on a schedule — from every fifteen minutes to every week, or the moment a file lands in a watched Vault folder — 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.
Capability builder
Solve it once. Everyone uses it.
A problem your team solves can become a reusable capability. A guided builder takes it from a working answer to something the whole organization can run.
Drafts and versions
Start from a draft, iterate, and keep every version — nothing is overwritten on the way to done.
Evaluated and certified
Evaluation runs test the capability against real cases, and certification marks it ready for others to rely on.
Installed and shared
Install it, share it, and the whole team runs the same method the same way.
Built once, used by everyone.
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
Knowledge that compounds
The core IP that makes the platform appreciate — not a copy of your files, but a living model of your fields and what your team has learned about 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.
A knowledge map of your fields
Wells, fields, reservoirs, formations, leases, completions, operators, basins, plays and more — organized the way an engineer thinks, and explorable in 3D, on a timeline, and back to the sources.
Study memory
What was learned, decided, tried, and rejected is kept at study level — so the next person, or the next run, starts where the last one stopped.
Deliverable lineage
Every report, deck, and PDF carries its source graph — open the lineage drawer and see exactly what it was built from.
An institutional asset no competitor can buy — because no competitor has your data and your decisions.
Agent evaluation
It grades its own work — and improves on it.
Every step an agent takes is judged by fast decision models — System One models — running through a gateway with zero data retention. The judgments don't just score the work; they change the environment the next job runs in.
Every step, judged
Fast decision models assess each agent step, through a gateway with zero data retention.
Its own improvement themes
The system surfaces where it went wrong, why, and what to change next — themes an engineer can read, not a score to squint at.
Recursive self-improvement
Those themes tune the environment its agents work in — with every job, not once a quarter.
More intelligence per dollar, and it grows with every job.
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 adds to its study memory and to a knowledge map 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.
Model Context Protocol
Connect your own agents.
Outside AI agents connect over the Model Context Protocol — with keys your administrators issue, scopes they choose, and every call on the record.
Scoped, admin-issued keys
Read scopes are granted per data area. Write access is a separate decision, made per key.
Governed reads and writes
Wells, production, wellbore, PVT, and simulation data within the key's scopes — with rate-transient and decline-curve results readable alongside.
Engineering compute
PVT, bottom-hole pressure, flow-path optimization, and simulation run as background compute jobs.
Every call logged
Every call an outside agent makes is logged, so what it read, wrote, or ran is always reviewable.
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 runs on the latest frontier models from the leading labs, a model per specialist (reservoir engineering on one, petrophysics on another) plus models for the core system roles, 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.