Elevate

What do they actually do

Elevate helps PE-backed roll-up platforms combine data from newly acquired businesses into a single, reliable view. They ingest exports, spreadsheets, and legacy systems, use a mix of large language models and rule-based pipelines to extract fields, standardize entities, enrich records, and load a consolidated warehouse for analysis (site and posts describe LLM- and agent-style workflows) (useelevate.dev; LinkedIn).

Customers receive a queryable set of consolidated tables (referred to on the site as "Albi tables"), KPI and board dashboards, and ongoing managed services to keep the data accurate. Current examples include commercial HVAC and restoration platforms; the company runs a hosted app and is an active YC Summer 2024 startup (useelevate.dev; YC profile).

Who are their target customer(s)

• PE-backed roll-up operators (CEOs/COOs of acquisitive platforms): Each acquisition brings different systems and spreadsheets, making it hard to get a single, trustworthy view of portfolio performance and slowing integration and reporting.
• M&A and diligence teams at roll-ups: Target company data is messy and fragmented, so validating revenue, margins, and operational metrics takes weeks instead of days, delaying deals and hiding risks.
• Finance and accounting leads at acquired businesses (controllers, bookkeepers): They manually clean, map, and reconcile inconsistent records after each acquisition, creating repeated work and disrupting month‑end close and roll‑up reporting.
• Heads of pricing, AR, and revenue operations at the platform: Inconsistent pricing rules, billing formats, and AR workflows across companies cause revenue leakage and slow collections because there’s no consolidated dataset to automate these processes.
• CFOs and board‑reporting owners at PE sponsors: Quarterly KPI and board packs require manual stitching of multiple sources, leading to slow, inconsistent reports and lower confidence in portfolio metrics.

How would they acquire their first 10, 50, and 100 customers

• First 10: Run high‑touch pilots with acquisitive platforms from existing networks and early inbound; sell a fixed‑scope integration plus managed‑services pilot that delivers one consolidated warehouse and a KPI dashboard (useelevate.dev; YC profile).
• First 50: Turn pilot work into a repeatable playbook: productize common connectors and a diligence pack, and partner with PE firms, M&A advisors, and roll‑up operators to sell fixed‑price integration packages and short diligence engagements (useelevate.dev).
• First 100: Scale with vertical‑specific GTM and productized upsells: embed in buy‑side diligence and sell‑side readiness, publish ROI in HVAC/restoration/pest, build channel partnerships, and sell AI apps (pricing, AR agents) as land‑and‑expand hooks (useelevate.dev; LinkedIn).

What is the rough total addressable market

Top-down context:

The initial focus is PE-backed roll-ups in services verticals (e.g., HVAC, restoration, pest) that need post‑acquisition data consolidation, analytics, and finance ops. As integrations become repeatable, similar roll-ups in adjacent services categories could be addressed without major product changes.

Bottom-up calculation:

If 300 active platforms in HVAC/restoration/pest spend about $150k per year on integration + managed services, the initial wedge TAM is roughly $45M; expanding to ~1,500 service‑heavy roll-up platforms at similar spend implies ~$225M potential. These figures are directional and assumption‑driven.

Assumptions:

• Average annual contract value of ~$150k per platform for integration, warehouse, dashboards, and managed services (scales with add‑ons).
• ~300 active roll-up platforms in the initial target verticals; ~1,500 across adjacent service categories in NA/EU.
• 100% of those platforms are potential buyers over time; pricing and scope comparable to today’s offering.

Who are some of their notable competitors

• Fivetran: Managed ELT connectors to centralize data from common SaaS and databases; strong for standardized sources but not tailored to messy legacy/spreadsheet ingestion or managed services.
• Airbyte: Open‑source ELT platform with a wide connector catalog; useful for building pipelines quickly, but requires teams to handle data cleaning, standardization, and ongoing operations.
• Tamr: ML‑based data mastering and entity resolution; overlaps on standardizing messy entities across sources, typically aimed at larger enterprise data quality programs.
• Palantir Foundry: Enterprise data integration and analytics platform used for complex consolidation; powerful but heavyweight for mid‑market roll‑ups and often requires significant services.
• West Monroe: Consulting firm with post‑merger integration and data engineering practices; competes via services‑heavy PMI and analytics implementations for acquisitive platforms.