Technology & Automation Research and Advisory
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Technology & Automation Research and Advisory

Strategic planning, market intelligence, product and technology advisory, investment research, and transaction support for technology innovators, automation companies, enterprise software and SaaS providers, and the PE and VC funds investing across industrial automation, robotics, IoT, and enterprise technology.

The Sector Today

The automation landscape is being restructured by the move from robotic process automation and narrow AI to agentic AI systems capable of reasoning across multi-step workflows. The distinction matters for investment and competitive analysis: companies that built their product and margin thesis on workflow automation at the task level are facing architectural displacement risk from agentic systems that can own the workflow end-to-end. Industrial IoT and robotics adoption in manufacturing and logistics is accelerating the physical layer of this transition, while enterprise software companies are racing to determine which parts of their feature set are defensible against AI substitution and which are not.
For PE and VC investors evaluating technology assets, the analytical challenge is in correctly identifying where the AI disruption is targeting the stack. A product that automates a task within a workflow is more exposed than a product that orchestrates the workflow itself. A platform with high switching costs, deep customer integration, and long contract durations buys time to adapt; one with low switching costs and annual renewal cycles is exposed on a shorter timeline. Getting the architectural assessment right is the work that separates a credible technology investment thesis from one that is simply optimistic about AI tailwinds.
For technology companies, the commercial pressure is in demonstrating that the product is on the right side of the disruption rather than the wrong side. Investors, customers, and acquirers are all asking the same question in different contexts: where does this product sit relative to the AI layer, and what is the defensibility of that position?
The Sector Today
The technology investment thesis that will hold up is the one that correctly identifies which layer of the stack the AI disruption is targeting and whether the company's competitive position is above or below that layer. Most current analyses get the what right and the where wrong.

Who We Serve

Emerging Technology Innovators and Growth-Stage Companies
Emerging Technology Innovators and Growth-Stage Companies
Emerging technology innovators, growth-stage technology companies, and deep-tech startups commercialising autonomous systems, AI platforms, robotics, and industrial IoT solutions that need market sizing, product-market fit analysis, technology maturity assessment, go-to-market strategy, and investor-ready materials to support fundraising and commercial scale.
Enterprise Software and SaaS Providers
Enterprise Software and SaaS Providers
Enterprise software companies and SaaS providers evaluating product positioning, build-versus-buy strategy, competitive differentiation, and AI integration roadmaps that need independent market intelligence and analytical support to navigate competitive displacement risk and sustain NRR.
Technology and Automation PE and VC Investors
Technology and Automation PE and VC Investors
PE firms, VC funds, and institutional investors with technology and automation mandates that need independent investment research, target screening, technology due diligence, portfolio monitoring, and transaction support across software, automation, robotics, and industrial technology investments.

What We Deliver

Strategic Planning & Market Intelligence · Technology & Product Advisory · Operational & Scaling Strategy · Strategic Transaction Advisory

Strategic Planning and Market Intelligence

Market sizing, go-to-market strategy, pricing analysis, and competitive intelligence for technology and automation companies assessing market opportunity, competitive position, and technology adoption dynamics.
Market sizing
Market sizing

TAM/SAM/SOM analysis for technology and automation markets using earnings calls, investor presentations, and industry research.

Go-to-market strategy
Go-to-market strategy

sales KPI analysis and competitive positioning assessment from investor commentary and market data.

Pricing strategy analysis
Pricing strategy analysis

peer benchmarking across pricing models, tier structures, and discount dynamics from expert interviews and call disclosures.

Technology trend tracking
Technology trend tracking

continuous monitoring of AI, robotics, agentic systems, and IoT developments from analyst reports, founder interviews, and investor commentary.

Competitive benchmarking
Competitive benchmarking

product roadmap comparison, adoption metric analysis, and strategic gap identification relative to market leaders.

Analytical Outputs We Produce

Agentic AI displacement analysis identifying architectural vulnerability in enterprise software stacks based on workflow position, switching cost, and contract structure.
Technology maturity and scalability assessments for automation, robotics, and AI platform investments.
TAM/SAM/SOM analysis for technology and automation markets using earnings calls, investor presentations, and industry research.
Pre-IPO financial models and investor materials for technology and automation fundraising mandates.
M&A target screening and technology due diligence reports for PE and VC mandates.
Competitive benchmarking reports covering product roadmap, adoption metrics, pricing, and strategic gap analysis.
Market entry roadmaps for technology companies expanding into India, Southeast Asia, and European markets.
Strategic insights for obesity drug market entry case study

Technology & Automation in Practice

Case Study

Agentic AI Displacement Risk Assessment for an Enterprise Software PE Investment

A PE fund evaluating an investment in a mid-market enterprise workflow automation software company commissioned Perusal Global for technology due diligence and agentic AI displacement risk assessment. The work covered the product's architectural position relative to emerging agentic AI systems, customer switching cost and integration depth analysis, NRR trend assessment against the fund's hold period, competitive landscape mapping of AI-native entrants in the same workflow category, and a scenario-based financial model reflecting three AI adoption curves affecting the target's revenue trajectory. The output informed the fund's investment committee submission and shaped the price adjustment in the final term sheet.

Frequently Asked Questions

Agentic AI disruption risk assessment covers three analytical layers. First, which workflows within the product's user base are candidates for agentic AI substitution? Agentic systems are most disruptive to multi-step, rule-based workflows with clear inputs and outputs, the kind generating recurring software subscription revenue. Second, what is the architectural position of the product relative to the AI layer? Products sitting above the AI layer at the workflow orchestration level are more defensible than those sitting below it at task execution level. Third, what are the customer switching cost and contract duration? High switching costs and long contract durations buy time for the incumbent to integrate AI capabilities before disruption reaches the customer relationship.

SaaS and enterprise software valuation uses revenue multiple, ARR growth rate, and net revenue retention as the primary framework, supplemented by a DCF modeling the transition from current growth rates to long-term steady-state margins. NRR is the most important single metric because it captures both expansion and churn simultaneously and is the most reliable predictor of long-term revenue durability. A business with NRR above 120 percent and strong gross margins will grow into its multiple over time; a business with NRR below 100 percent is shrinking in its existing customer base regardless of new logo growth. The Rule of 40 score provides a single metric for benchmarking capital efficiency across the peer set.

Technology maturity assessment for an automation investment covers four dimensions. Deployment evidence: is the technology deployed at commercial scale with paying customers, or at pilot scale with limited real-world validation? Performance data: does the performance in commercial deployment match the performance claimed in the investment materials, accounting for the difference between controlled test environments and operational conditions? Integration complexity: how difficult is it to integrate the technology into the customer's existing operational environment, and does that complexity create sales cycle length and implementation risk that affects the financial model? Competitive positioning: is the technology meaningfully differentiated from alternatives, and is that differentiation defensible through IP, proprietary data, or customer switching cost?

Technology due diligence covers code quality, scalability, IP ownership, and technology debt. Code quality and maintainability: is the codebase documented, tested, and structured for efficient development beyond the original founders? Scalability: can the architecture handle projected user growth and transaction volume, and what is the investment required? IP ownership: are there third-party code dependencies, open-source licence obligations, or employee IP assignment gaps affecting the acquirer's ownership? Technology debt: what proportion of the engineering roadmap is consumed by maintenance rather than product development? A business where more than forty percent of engineering time is maintenance has a technology debt problem affecting both near-term product velocity and post-acquisition integration cost.

A technology market entry assessment for India or Southeast Asia covers market sizing, competitive landscape, regulatory environment, go-to-market structure, and a financial model for the entry scenario. Market sizing: total addressable spend in the relevant technology category in the target geography, the competitive set already serving that market, and the realistic addressable market for the entrant's specific product and price point. Regulatory environment: data localisation requirements, sector-specific technology regulations, and government procurement rules that affect the product's deployability. Go-to-market structure: whether direct sales, channel partnership, or platform distribution is most capital-efficient for the target market. The financial model covers the capital required to reach profitability in the market and the payback period at different penetration rate assumptions.

A technology M&A target screening mandate typically covers universe definition, target identification and preliminary assessment, shortlist refinement, and investment brief preparation for the top candidates. Universe definition establishes the technology sub-sector, geography, revenue stage, and specific capability or technology the acquirer is targeting. Target identification uses a combination of industry databases, technology mapping, patent landscape analysis, and expert network intelligence to build a comprehensive list. Preliminary assessment covers revenue size, funding history, technology differentiation, customer base, and strategic fit. The shortlist is refined based on the acquirer's specific criteria and an investment brief is prepared for each top candidate. Most mandates of this scope are completed within four to eight weeks depending on the breadth of the universe.

Further Reading

Selected research and commentary on the topics that matter most to technology investors, enterprise software strategists, and automation-focused funds.
Agentic AI and Enterprise Software: Which Parts of the Stack Are Architecturally Exposed?
Agentic AI and Enterprise Software: Which Parts of the Stack Are Architecturally Exposed?
SaaS Valuation in 2025: NRR, Rule of 40, and the AI Disruption Discount
SaaS Valuation in 2025: NRR, Rule of 40, and the AI Disruption Discount
Technology M&A Due Diligence: Why Code Quality and Technology Debt Belong in the Investment Thesis
Technology M&A Due Diligence: Why Code Quality and Technology Debt Belong in the Investment Thesis
For broader research on financial modeling, investment research, and strategy consulting, visit our resources section.
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Ready to Work?

The first conversation is about the specific decision your team is facing: a technology investment thesis that needs validating, a software product that needs competitive positioning assessment, a market that needs sizing before entry, or a transaction that needs due diligence. We will tell you precisely how we approach it.
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Perusal Global is a strategic, technology- and AI-driven research and advisory partner trusted by investment banks, financial institutions, corporates, private funds, and high-growth enterprises across the United States, Europe, the GCC, and India.

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