Read the commercial evidence
Process machine-readable agreements in a private Azure AI environment and preserve the source language behind every proposed field.
AI-Powered IT M&A Execution PlatformMergeVista Intelligence
AI that connects contract evidence to execution decisions.
Move from an uploaded agreement to governed products, license entitlements, inventory relationships and readiness action—without separating the AI output from its source or the people accountable for approving it.
LIVE PRODUCT VIEW Illustrative sample dataSOURCE-GROUNDED REVIEW
01Source-grounded extraction02Private Azure AI processing03Confidence + rationale04Human approval
One connected intelligence chain
Do more than extract contract fields.
The value comes from carrying trustworthy commercial intelligence forward—into the products, rights, technology records and execution decisions that determine whether the transaction can operate.
Extract what execution teams need
Identify contract terms, dates, renewal and consent requirements, disposition signals, products, editions, license metrics and quantities.
Normalize products and entitlements
Reconcile product names and aliases, connect contractual rights to a governed catalog and retain the agreement and evidence from which each entitlement originated.
Connect rights to deployed technology
Propose relationships between products and deal inventory—including applications, servers, network devices and users—with confidence, rationale and supporting evidence.
Turn relationships into action
Expose missing rights, unallocated links, over-deployment and unresolved coverage so teams can make defensible Day 1, migration and exit decisions.
Platform capabilities
Intelligence designed for governed IT M&A execution.
Each capability produces structured, reviewable information that remains connected to transaction context and accountable ownership.
01Contract intelligence
Extract fields that remain connected to their source
MergeVista captures critical commercial terms and product-level information while retaining the supporting clause or snippet, confidence level and review state.
- Contract identity, dates, renewal, assignment, change-of-control and consent terms
- Product, edition, quantity, metric and inventory-match signals
- Grounding checks reject output that cannot be traced to the uploaded document
02Product normalization
Create one commercial view of every product and service
AI-assisted normalization brings inconsistent product references into a governed catalog while preserving aliases, vendor context and the original extracted name.
- Canonical product records with vendor, edition, category and product type
- Approved aliases improve reconciliation across documents and inventories
- Lifecycle, scope and strategy remain explicit business decisions
03License intelligence
Connect contractual rights to the products they govern
Entitlements retain purchased quantity, assigned quantity, metric, dates, source reference, coverage and disposition so technical execution stays aligned with commercial rights.
- Agreement-to-product-to-entitlement traceability
- Inherited disposition with controlled, reasoned overrides
- Day 1 coverage and reconciliation status visible in context
04Inventory reconciliation
Find where commercial products exist in the deal inventory
MergeVista compares the product catalog and approved aliases with transaction inventory, then proposes potential relationships for accountable review.
- Candidate matches include confidence, rationale and evidence
- Links can be allocated to a specific entitlement
- Manual linking remains available when teams already know the relationship
05Exception detection
Surface the gaps that can disrupt Day 1 or TSA exit
The connected model evaluates contractual rights, approved inventory links and reported consumption to identify actionable commercial and deployment exceptions.
- Missing entitlements for quantity-based products
- Consumption not reported or exceeding contractual rights
- Approved inventory links not allocated to an entitlement
06Human governance
Keep accountable people in control of every consequential decision
AI creates proposals—not final transaction decisions. Reviewers can correct extracted values, approve or reject matches, provide reasons and preserve the resulting history.
- Pending-review status for extracted information
- Explicit approval or rejection of reconciliation proposals
- Reason-required removal of approved inventory links and auditable actions
Governed by design
Private processing. Grounded output. Accountable decisions.
MergeVista uses customer-enabled private Azure AI processing with managed identity. AI execution requires explicit authorization, proposed outputs are validated against allowed records and source evidence, and consequential changes remain subject to human review.
Tenant-controlled AI
AI processing can be enabled by customer tenant and runs through a privately configured Azure environment.
Evidence before assertion
Extracted values retain source snippets; proposed inventory matches carry confidence, rationale and evidence.
Proposal before decision
Reviewers approve, reject, correct or remove relationships with the decision history preserved.
The responsibility boundary
AI accelerates analysis. People remain accountable.
- Extracting structured information from source documents
- Normalizing inconsistent product references
- Proposing product-to-inventory relationships
- Highlighting potential licensing and coverage exceptions
- Whether extracted information is correct and approved
- Which inventory relationships become authoritative
- Product scope, disposition and Day 1 coverage
- Commercial, migration and TSA exit actions
See contract intelligence become execution intelligence.
Explore the complete path from agreement evidence to governed inventory and readiness decisions.