The commercialization playbook doesn't change.
The execution does.

I build the ICPs, buying-committee maps, techno-economic models, and pipeline infrastructure that get hard-tech products into multinational supply chains.

From Proof-of-Concept to Commercial Traction

16 years commercializing technologies across agriculture, industrial bioprocessing, climate tech, and advanced materials.

Commercialization Strategy

Translating platform technology into clear product concepts, go-to-market plans, and commercial roadmaps. I help deep tech teams identify which applications to pursue first and how to position them for the customers and markets that matter.

Techno-Economic Analysis

Building the models that answer the hard question: can this work at scale, and will anyone pay for it? I develop techno-economic analyses that ground commercial decisions in real cost structures, helping secure funding and partnerships with industrial players.

Sales Infrastructure & Enablement

Building the selling system from scratch: ICP definitions, discovery interview playbooks, objection maps, pipeline architecture, and CRM setup. Grounded in Strategic Selling methodology, adapted for deep tech.

Plus partnership development & enterprise sales execution and market intelligence work — full detail on the services page.

Common Challenges Across Deep Tech Sectors

Deep tech commercialization follows a structural playbook regardless of sector. The challenges are identical; the manifestations are different.

Challenge Agricultural Biotech Industrial Decarbonization Bioprocessing & Biomanufacturing Advanced Materials & Chemicals AI & Sales Technology
Navigating Buying Committees Regulatory affairs leads technical evaluation; supply chain directors control budget; agronomists shape adoption Multiple economic buyers across energy, procurement, and operations with competing sustainability metrics Quality assurance and manufacturing engineering determine feasibility; plant directors control capex; regulatory flags unknowns Materials science teams slow-gate adoption risk; manufacturing engineers require 18-month proof-of-concept timelines VP Sales owns pipeline and quota; VP Engineering owns technical validation and integration risk
Quantifying Pre-Commercial Value Yield and shelf-life gains compound unpredictably across growing conditions; farmer economics vary by geography and scale Capex payback periods depend on energy price, carbon pricing mechanism, and grid composition that shift annually Cost per liter at 500L differs radically from production scale; process yields at pilot don't predict manufacturing yields Material performance in lab conditions doesn't translate to production environment; qualification cycles run 24+ months Revenue impact depends on deal velocity that sales team can't yet deliver; competitive dynamics shift quarterly
Regulatory & Compliance Timeline Seed approval timelines extend 7-10 years; regulatory pathway varies by crop, country, and trait stacking Energy infrastructure regulations are regional and changing; environmental permitting adds 12-36 months to deployment timeline Bioburden protocols, shelf-life testing, and regulatory classification delays scale-up by 18+ months before pilot Chemistry and material testing consume 2+ years before industrial-scale testing; environmental compliance varies by geography Data privacy and security certifications gate enterprise adoption; regulatory frameworks shift as AI governance evolves
Incumbent Gatekeeper Dynamics Distribution networks control market access; incumbent seed companies have regulatory relationships and farmer trust spanning decades Incumbent energy infrastructure has sunk capex and existing supply relationships; utilities move slowly due to capital intensity COGS leaders have established relationships with CDMOs; suppliers have long-term contracts with penalty clauses; switching requires supply chain redesign Established chemical suppliers own qualification relationships and have legacy performance data; switching requires design validation testing Enterprise sales orgs have existing tool stacks and vendor consolidation pressure; replacing an incumbent CRM requires migration and retraining
Scale-Up Economics Licensing agreements cap your upside unless you own supply chain; agronomic data requires multi-season field trials in multiple geographies Capital requirements ($100M+ for manufacturing scale) require strategic partnership or dedicated funding; operations are geographically constrained CRAM costs and outsourcing propensity are tier-dependent; fermentation scale-up introduces new contamination and process control risks Capex for pilot-to-production jumps 100-500x; material costs depend on sourcing, purity, and supply continuity at scale Customer acquisition cost for sales software may exceed lifetime value; retention depends on integration depth and switching costs

Each cell represents where the commercialization playbook requires sector-specific execution. Market sizing, buying committee mapping, TEA modeling, competitive positioning, and sales infrastructure all adapt to these constraints

Science Doesn't Sell Itself

If you're sizing a market, mapping your buying committee, modeling your path to commercial scale, or building a sales system for a complex product, let's talk about where you are and what you need to figure out next.