We evaluate infrastructure, AI architecture, vendor claims, and governance frameworks — then deliver a clear verdict to your investment committee. Not a 200-page deck. A direct, defensible finding.
Email or complete our short intake form with the target, the question on the table, and your deal timeline.
In 90% of cases we respond within 15 minutes to confirm scope, flag any conflicts, and agree on next steps.
We agree on a clear, fixed fee before any work begins. Minimum one hour. No surprises.
If we do not deliver a defensible, IC-ready finding, you do not pay. Outcome-based means exactly that.
Every engagement begins with an alignment call. We use it to understand the deal and confirm fit. If we are not the right match, we say so directly — no charge.
No marketplace of third-party consultants. You are not routed to an unvetted specialist pulled from a network. The people who scope the engagement are the people who run it.
Technical + Commercial + Organizational. We go beyond technical diligence — covering business diligence, org structure, market dynamics, vendor recommendation, and buying criteria in a single engagement.
Operator-level depth on every vendor class. Legacy incumbents, AI-native startups, and frontier model labs — we have inside-operator perspective, not surface-level feature comparisons.
Outcome-based pricing. No outcome equals no charge. We align our incentives directly with the value we create for you. Simple as that.
A clear, repeatable process — structured around your deal timeline, not ours.
We understand the target, the timeline, and the specific question the IC needs answered. If we are not the right fit, we say so — no charge.
Your firm's standard NDA or our clean 2-page mutual. Scope is fixed in writing before any proprietary materials are reviewed.
We assess architecture, market position, org execution risk, vendor licensing, and competitive moat — at the depth an operator brings, not a generalist.
A direct written finding — defensible, dangerous, or conditional — structured for a 1-hour investment committee briefing. No hedged language.
De-risk platform acquisitions and buyouts with operator-level engineering diligence, scalability review, technical debt assessment, and post-close integration risk mapping.
Surface hyperscaler lock-in, evaluate migration paths to alternative bare-metal compute, and size hardware capacity run-rates to inform post-close margin assumptions.
Separate marketing claims from production reality by reviewing model codebases, prompt pipelines, accuracy scores, and core architectural dependencies.
Validate early-stage technology defensibility and engineering scaling strategy before committing growth capital.
Review early-stage software architecture, microservices design, compute-resource dependencies, and model choices ahead of an investment committee review.
Check the claimed accuracy of specialized legal-tech, tax-tech, and quantitative extraction engines against existing enterprise platforms to test the real moat.
Give public-equity models and discretionary desks granular, operational software tracking and technical platform read-throughs.
Track structural software shifts, container-orchestration adoption, and compute-fabric trends that signal momentum in public tech equities.
Run targeted platform reviews and check deployment trends under a documented, auditable compliance framework.
Strengthen M&A sell-side positioning, advisory pitches, and equity research with independent technical validation.
Provide a transparent technical read on a target's IP portfolio, verifying algorithms and code health to support cross-border underwriting requirements.
Compare target system architecture against emerging enterprise standards to isolate genuine structural value drivers for a fairness-opinion review.
Ground high-level transformation recommendations in an accurate, reality-tested technology assessment.
Check modernization and cost-reduction plans against real software constraints, so the recommended target state matches operational limits.
Run independent RFP validation and evaluate middleware integration claims to head off vendor lock-in before deployment begins.
Bring independent engineering judgment to digital modernization, AI adoption, and infrastructure transition decisions.
Assess sovereign configuration options, evaluate proposed automation pipelines, and benchmark multi-node cluster designs for enterprise model fine-tuning.
Map risk vectors against the actual distributed-data footprint, assess internal-control readiness, and review regulatory prompt compliance.
We cover the full spectrum of technology diligence — from AI infrastructure and frontier model risk to legal-tech workflows, tax filing platforms, court systems, GRC, and security. Every engagement draws on operator-level knowledge built across 30 years at Thomson Reuters, RBC, Hitachi, Hewlett-Packard, and top-tier hyperscaler engagements.
Foundation models, frontier models, GPU infrastructure, AI hyperscalers, vendor licensing, and neo-cloud providers across SMB and Enterprise tiers.
Agentic AI for legal workflows, e-filing systems, contract lifecycle management, RAG-based research platforms, and legal operations transformation.
Tax filing platforms, K-1 and partnership tax data flows, indirect-tax engines, OCR accuracy validation, and cross-border filing compliance.
Governance, Risk, and Compliance platforms, continuous attestation, audit-trail integrity, and regulatory exam readiness for financial institutions.
Multi-tenant isolation, identity and access management, SBOM analysis, privilege-escalation reviews, and vendor security posture assessment.
US court case management procurement evaluation, e-billing, payment systems, document security, redaction automation, and peak-load performance.
Vertical software market dynamics, competitive landscape analysis, AI-native entrant benchmarking, vendor recommendation, and buying-criteria frameworks.
Regulatory compliance technology, evidence management, data lineage, control mapping, and cross-jurisdictional compliance posture reviews.
Evaluating multi-node scalability, bare-metal provisioning, and alternative GPU cluster options. Covering foundation models, frontier models, base models, AI hyperscalers, and vendor licensing across SMB and Enterprise.
Auditing InfiniBand and RoCEv2 topologies for node-to-node latency issues. We check scheduling layers, memory bandwidth limits, and thermal behavior under distributed inference load.
Reviewing multi-tenant isolation by testing container orchestration controls and checking firmware configuration for hardware-level isolation gaps.
Reviewing text-extraction workflows, citation-validation pipelines, and performance limits inside enterprise legal platforms — including e-filing, e-billing, and agentic AI deployments.
Auditing retrieval-augmented generation systems on proprietary document sets — chunking mechanics, lexical overlap, and index-update triggers — to flag hallucination risk during discovery.
Benchmarking the reliability of flagship enterprise platforms — including Westlaw, Practical Law, and CLEAR configurations — against current performance expectations.
Checking programmatic calculation trees, multi-jurisdictional data ledgers, and transactional codebases — including K-1 filings, Schedule K-1 data flows, and partnership tax structures for PE fund acquisitions.
Stress-testing tax calculation engines under high-throughput transaction flows. We trace parsing layers and currency-conversion logic to flag ledger discrepancies before they compound.
Evaluating OCR and table-parsing accuracy within enterprise ERP integrations to isolate downstream processing flaws early — before a filing period exposes them.
Mapping control hierarchies, data lineage, and governance baselines against how the system actually operates — not how it is described in policy documents.
Tracing data flow from intake through production state changes, checking permission enforcement against institutional reporting requirements.
Assessing how ready a self-auditing control design is to replace manual log-gathering, and whether the evidence trail will hold up to board review.
Auditing the software integrity, alert-ingestion rules, and tracking engines used by regulated financial entities.
Stress-testing regulatory filing connectors and validation rules, checking API payload handling under market-spike volume.
Evaluating storage persistence and access controls to confirm compliance logs stay tamper-evident against privileged-account access.
Reviewing identity-management design, token validation, and container security controls across enterprise ecosystems — including e-billing and payments infrastructure.
Analyzing sidecar network configuration, identity-proxy design, and runtime alert logs to flag credential-manipulation risk in multi-tenant environments.
Scanning production code for software-bill-of-materials anomalies and verifying base-image origins against known provenance to surface hidden supply-chain exposure.
Independent technical evaluation of US court case-management platforms — covering document security, e-billing, payments infrastructure, and peak-load performance before procurement decisions are made.
Reviewing message-queue architecture, database locking design, and disaster-recovery documentation against contractual RPO/RTO commitments before a multi-year award is signed.
Auditing access-control logic and redaction-automation pipelines against the jurisdiction's public-record rules to surface gaps that could expose sealed case materials.
Vertical software market dynamics, competitive landscape analysis, and buying-criteria frameworks for investors and operators evaluating software assets — from SMB to Enterprise.
We map the full vendor ecosystem, assess each competitor's AI roadmap maturity, and benchmark the target against both legacy incumbents and AI-native challengers entering from adjacent categories.
Developing structured buying frameworks from a customer decision-maker perspective — covering vendor licensing models, total cost of ownership, and switching-cost analysis.
Toronto-based. US and UK clients. We combine deep technical intelligence with institutional commercial judgment — the kind that comes from having sat on both sides of the table.
Varun Kalsi is a 30-year industry leader in product, infrastructure, and AI — having held C-suite and senior executive roles at some of the world's most complex technology organizations across financial services, legal, tax, and enterprise platforms.
At Thomson Reuters, he led platform strategy across AI, Legal, and Tax technology — the exact ecosystem Lexaxis advises on today. At RBC, he headed AI strategy and deployment for one of North America's largest financial institutions. As Managing Director at Hitachi, he carried full enterprise platform responsibility across global operations. At Hewlett-Packard, he held senior platform leadership across large-scale infrastructure programs.
Beyond his employer roles, Varun has delivered advisory engagements directly for leading hyperscalers and AI labs — including AWS, Google Cloud, Anthropic, CoreWeave, and OpenAI — giving Lexaxis rare, inside-operator perspective on the AI infrastructure market that most advisory firms cannot access.
This breadth across operator, advisory, and institutional roles is not incidental. It is the foundation of what Lexaxis delivers — and why our findings carry weight in investment committee rooms.
We advise US venture capital and private equity funds on technical viability, AI differentiation, and vendor risk. In high-stakes, 1-hour briefings, we cut through marketing fluff to tell investment committees whether a technology asset is defensible or dangerous.
Active across the US, Canada, UK, Spain, and Singapore. We do not take positions in companies we evaluate and carry no referral arrangements with vendors we assess.
Real delivered engagements alongside illustrative scenarios that demonstrate methodology. Each links through to the full challenge, approach, and result.
Lexaxis Advisory Partners is growing from a founder-led practice into a small team of senior operators. We are looking for one more person who has sat on the buying side of the table.
Compensation and equity structured for a founding-team hire — details discussed directly.
Apply — info@lexaxisadvisory.comDescribe the target, the timeline, and what the finding needs to support — an IC memo, a board deck, an RFP decision. You will hear back from the person who will actually run the review.
Every engagement begins with a brief alignment call. If we are not the right fit, we say so directly — no charge.
Engagements span the US, Canada, UK, Spain, and Singapore. NDA available before any proprietary materials are reviewed.