01
VDRs hide critical signals.
Technical reports, legal agreements, production data and fiscal terms are scattered across folders, appendices and spreadsheet tabs.
Now launching
AI-native due diligence for energy M&A.
Aigis helps upstream investors, operators and advisors move from VDR complexity to evidence-backed investment judgement faster.
VDR intelligence
Specialist DD
Buyer case
Evidence trail
Built for upstream O&G
Source-grounded outputs
Local-first deployment posture
Aigis diligence workspace
Live preview
Transaction data room
Mapped
VDR coverage, gaps and priority diligence routes
VDR mapcomplete
Modelparsed
Claimsverifying
Reportdrafting
VDR to board packDesigned around the complete transaction workflow, not single-document chat.
Source-groundedQuantitative claims are tied back to source data, model logic and evidence trails.
Built for upstreamDomain playbooks cover reserves, wells, fiscal terms, ARO, legal and commercial risks.
Human-ledAigis force-multiplies experienced deal teams; judgement remains with the user.
The problem
Diligence risk compounds when teams triage under pressure.
Energy transactions are document-heavy, model-heavy and judgement-heavy. Traditional review processes force teams to choose between speed and coverage.
02
Financial models are bespoke.
Seller models rarely follow a clean schema. Understanding assumptions, scenarios and output logic takes expert time.
03
AI summaries are not enough.
For serious diligence, teams need structured extraction, cross-document reasoning, verification status and an audit trail.
The workflow
From data room to decision workspace.
Aigis follows the way energy deal teams work: map the VDR, extract the facts, build the diligence view, verify the claims, and package the outputs for decision makers.
VDR intelligenceMapping stage
Map the VDR
Turn a raw transaction data room into a diligence map that shows coverage, gaps and the fastest route to the next questions.
Output
VDR quality reviewFolder coverage, duplicate material, missing workstreams and data-room hygiene issues surfaced early.
Output
Document request listTargeted follow-up asks based on gaps against upstream diligence categories.
Capability
Domain-informed data room searchSearch and retrieval tuned for reserves, wells, fiscal terms, ARO, legal and commercial topics.
Why Aigis is different
Verification before persuasion.
Generic AI can write a plausible answer. Aigis is designed to show what the answer is grounded in, what can be verified, and what still needs expert review.
MARKO: source-grounded diligence.
MARKO is Aigis's high-level verification layer: it structures outputs around evidence packets, financial model data, source citations and review status.
DB-verified quantitative claims where extracted data is available
Source-cited findings linked back to the VDR
Unverifiable items surfaced for human judgement
Built for domain-specific work.
Upstream diligence has its own language: working interest, NRI, reserves classes, LOE, ARO, fiscal regimes, PSC terms and model scenario logic. Aigis is built around those realities rather than generic document retrieval.
Upstream oil & gas diligence playbooks
Financial, technical, legal and commercial workflows
Human-in-the-loop review boundaries for high-stakes decisions
What teams get
Decision materials, not just answers.
Aigis turns unstructured transaction material into diligence outputs that can be reviewed, challenged and used by deal teams.
01
VDR gap analysis
Coverage view across standard upstream diligence categories.
02
Board-level DD report
Structured findings with evidence status and diligence gaps.
03
Buyer-case workspace
Model-informed risk, sensitivity and investment-case views.
04
Follow-up Q&A
Ask targeted questions against the deal context and outputs.
Who it is for
Built for the energy deal table.
The first Aigis workflows focus on upstream oil & gas transactions, where document volume, technical complexity and financial model risk collide.
Investors
Energy PE and funds
Support the full diligence cycle, from initial screening through specialist DD workflows, buyer-case assumptions and investment committee materials.
Operators
Corporate development
Support acquisition screening, VDR review and board decision materials.
Advisors
Transaction teams
Force-multiply technical, financial, legal and commercial diligence workstreams.
Trust posture
Designed for sensitive transaction data.
Energy M&A data rooms contain commercially sensitive material. Aigis is designed around controlled deployment, auditability and human governance.
Local-first and single-tenant by design.
Aigis is not positioned as an open consumer chatbot. It is built for controlled diligence workflows where data handling, evidence trails and review boundaries matter.
Deployment postureLocal-first / controlled
Data room handlingDeal-scoped workflows
Output governanceEvidence status + review flags
Buyer motionTechnical briefing first
Opening the conversation
Bring AI-native diligence to the full energy M&A cycle.
If you work in upstream investing, corporate development, advisory, reserves, legal DD or transaction services, we would value your perspective.