Corp Dev Director · persona overview
Corp Dev: Building an AI Infrastructure Acquisition Shortlist
How a hyperscaler Corp Dev director moved from sector-level scouting to a 4-target shortlist in 3 days using engineering-signal data.
A Corp Dev director at a Fortune 100 cloud platform needed to build a shortlist of 4 AI infrastructure acquisition candidates for an internal strategy review. The platform's leadership had set a 90-day window to identify and approach targets before competitive bidding hardened pricing. Traditional banker books were not yet circulating for any of the most interesting targets.
Workflow
- 1
Sector framing
Started at the /sector/ai-infra hub to understand the engineering-acceleration shape of the AI infrastructure category. Read the why-it-matters editorial, scanned the tracked companies, identified the 8 most-active orgs in the sector.
- 2
Per-company deep dive
Drilled into each tracked org's /signal/[slug] page to read engineering momentum, contributor counts, and language-bias signals. Cross-referenced against existing acquirer pattern (own M&A history at /acquirer/[platform]) to filter for strategic fit.
- 3
Side-by-side comparison
For top 4 candidates, compared /signal/[slug] pages side by side on stage, momentum, public repos, and language bias. Surfaced engineering-team-shape differences that affected integration cost models.
- 4
Trend cross-reference
Checked /trend/llm-inference-providers-2026 to validate that the shortlist matched the broader category leadership. Confirmed the editorial roster aligned with the side-by-side comparisons.
- 5
Geographic filter
Filtered final 4 candidates through /city/[slug] pages, checked HQ locations against acquisition integration constraints (work-authorization, time-zone overlap with engineering centers).
Outcome
The Corp Dev director presented the shortlist to leadership 4 days after starting the research, with engineering-signal context for each candidate and a recommended approach order. Leadership approved 2 exploratory outreach conversations within the 90-day window, both initiated 4-6 weeks before competitive bidding emerged.
Lessons & takeaways
- Engineering-signal data is most useful when paired with the acquirer's own M&A pattern, it accelerates the shortlist phase but does not replace strategic fit analysis.
- Per-company /signal pages should always be cross-referenced against /sector and /trend pages before drawing conclusions.
- Reading candidate /signal pages side by side is the highest-leverage step for shortlist construction.
Frequently Asked Questions
Is this case study a real customer?▾
No. This is an illustrative composite of workflows we observe in onboarding and demo conversations. Names, specific deals, and identifying details are omitted by design. The structure of the workflow (what URLs the persona uses, what questions they ask, what action they take) is representative.
What persona does this scenario match?▾
Corp Dev Director. For the full persona-specific overview, see /for/corp-dev.
How long did it take to build the acquisition shortlist?▾
In this composite scenario, the Corp Dev director moved from sector-level scouting to a 4-target shortlist in about 3 days, presenting to leadership on day 4, inside a 90-day window before competitive bidding hardened pricing.
Which pages does Corp Dev use to build an acquisition shortlist?▾
The workflow runs /sector/[slug] for category framing, /signal/[slug] for per-company engineering momentum and side-by-side comparison, /trend/[slug] to validate category leadership, and /city/[slug] to filter for integration constraints.
Does engineering-signal data replace strategic-fit analysis?▾
No. It accelerates the shortlist phase but is paired with the acquirer's own M&A pattern (see /acquirer/[platform]). Strategic fit, integration cost, and approach order are still assessed separately.
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