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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallEvaluate a deep-tech startup as a chain of linked claims, not as a single technology score. The core question is whether the underlying science works, whether an engineered product or service can deliver that performance repeatedly at an acceptable cost, and whether a specific customer can buy, deploy, operate and scale it under real regulatory, supply and financing constraints.
Keep evidence, assumptions and forecasts separate. For every material uncertainty, record the evidence available now, what remains unknown, who owns the answer, the cheapest decisive test, its cost and timing, and the decision that follows. A high Technology Readiness Level (TRL) can describe technical maturity without proving market demand, economic viability or delivery capability.
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Start with the decision, not the technology
Technical diligence changes depending on what you are deciding. An investor considering a seed round needs to know which experiments justify the next financing step. A corporate partner may need confidence that integration will work at a particular site. A licensee needs a defensible right to use the invention. A procurement team needs evidence of performance, quality, safety and support. State the decision before reviewing data.
Define the company and product boundary
Write down the business model, intended customer, geography, product or service boundary and current stage. Clarify whether the company sells hardware, a process, software, a consumable, a project-development service, recurring operations or a combination. Many apparent technology successes move risk into an adjacent activity—specialized installation, feedstock preparation, calibration, maintenance or project finance—that is outside the laboratory demonstration.
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Set stage-appropriate success criteria
Define technical success and commercial success separately. At an early research stage, technical success might mean repeatable performance under a stated test protocol. At a pilot stage, it may require reliable operation with realistic inputs and a measured cost path. Before a broad rollout, success also requires qualified production or service delivery, customer acceptance, regulatory approval where applicable and a credible margin after support and replacement costs.
Distinguish a company-level investment question from a project, licensing, partnership or procurement question. The same evidence can be adequate for one decision and inadequate for another.
Build an evidence map before assigning a risk score
Translate the pitch into claims that can be tested. Typical claims include a performance advantage, a lower cost, a proprietary mechanism, a manufacturing route, a safety profile, a customer benefit and a deployment schedule. For each claim, identify the evidence type and its limitations.
Separate evidence from assumptions and forecasts
- Observed evidence: traceable test results, operating records, signed contracts, issued rights or documented approvals.
- Assumptions: expected yield, utilization, input price, production volume, service life, customer conversion or regulatory timing.
- Forecasts: projected unit cost, margin, market share, capacity and financing needs derived from the first two categories.
Ask for the original data rather than a slide-level conclusion. A useful technical record identifies test conditions, sample size, controls, failures, exclusions, repeatability, measurement uncertainty and who performed the work. A useful commercial record identifies the buyer, budget owner, commitment, alternatives, procurement path and conditions that must be met before payment.
Classify the operating environment
Mark what has only been modeled, what has been demonstrated in a controlled laboratory, what has been validated with relevant inputs, and what has operated in the intended environment. A result in a clean laboratory feed or short demonstration may not survive contaminants, weather, duty cycles, maintenance intervals, operator variation or integration with adjacent equipment.
Assess science risk and engineering risk separately
Science risk asks whether the claimed mechanism works at all and under which conditions. Engineering risk asks whether a product can be built, integrated, operated, maintained and reproduced at the required reliability. A company can have low science risk and high engineering risk, or the reverse.
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Questions for the scientific claim
- What physical, chemical, biological or computational mechanism produces the claimed result?
- Which variables define the valid operating window, and how sharply does performance fall outside it?
- Were controls and negative results reported, or only the best runs?
- Have independent people reproduced the result using the same protocol?
- Does the result depend on an unprotected material, dataset, algorithm, organism, process step or individual expert?
Questions for the engineered system
- Can the design tolerate expected variation in inputs, temperature, pressure, network conditions, user behavior or other loads?
- What fails first, how is failure detected, and how quickly can the system recover?
- What are the maintenance, calibration, replacement and service requirements?
- Are quality tolerances and test methods defined for production units, not just prototypes?
- Which interfaces with customer equipment or infrastructure create integration risk?
Use TRL as an evidence organizer, not a verdict
Technology Readiness Levels help describe the environment in which evidence was generated. The UK government technology-transfer guidance places TRL 4–6 broadly around validation or demonstration in conditions increasingly close to intended use, while TRL 7–9 progress through operational demonstration, qualification and successful use. The exact label matters less than the underlying test record.
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TRL does not establish customer adoption, unit economics, regulatory approval, manufacturing capacity or delivery capability. The U.S. Government Accountability Office’s Technology Readiness Assessment Guide, published as an exposure draft, says readiness assessments can illuminate concerns and support mitigation discussions but “do not eliminate technology risk.” Treat a TRL as a point-in-time description of technical evidence, not as a probability of investment success.
Test scale-up and techno-economics together
Scale-up is where laboratory performance becomes an operating and financial question. Require a bridge from the demonstrated configuration to the commercial configuration: size, throughput, materials, suppliers, controls, staffing, maintenance and expected life.
Rebuild the economic model
Use a transparent model that links each technical variable to cash cost and revenue. At minimum, expose:
- yield, uptime and utilization;
- input, energy, consumable and waste costs;
- capacity, cycle time and deployment time;
- capital equipment, installation and commissioning costs;
- labor, maintenance, software, logistics and replacement costs;
- selling price, contract terms, warranty or performance obligations; and
- financing costs and working-capital requirements.
Do not accept one optimistic base case. Stress the variables that can change the investment conclusion. Test lower yield, slower throughput, higher input prices, longer installation, greater service labor, lower utilization and a lower selling price. Show the break-even condition for each critical variable and identify which experiment or customer commitment would reduce the uncertainty.
Connect milestones to economics
Every technical milestone should unlock a measurable economic consequence. A longer component life may reduce replacement cost; a wider input tolerance may lower feedstock expense; a faster cycle may increase annual revenue; a simpler assembly may reduce capital and quality risk. If a milestone does not change a cost, capacity, reliability, price or adoption constraint, explain why it is still necessary.
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The I-C3 2026 field guide treats techno-economic assessment, scale-up risk, milestone order and risk registers as connected technical-diligence topics. Use that sequence to expose dependencies: a pilot may be pointless if the required material cannot be supplied, and a manufacturing investment may be premature if customer qualification has not started.
Validate customers and the path to adoption
Commercial risk is not the same as market-size risk. Identify the person who experiences the problem, the person who controls the budget, the person who approves technical or safety requirements and the organization that operates the solution. They may be different.
Establish a real buying case
- What urgent problem is being solved, and what happens if the customer does nothing?
- Which incumbent, workaround or competing technology receives the budget today?
- What measurable benefit justifies switching, including integration and training costs?
- What procurement, cybersecurity, quality, insurance or financing approvals are required?
- How long does a pilot, qualification, installation and paid conversion normally take?
Letters of interest and pilot participation are useful but limited evidence. Record who signed, whether the document is binding, what quantity or site is specified, which performance conditions apply, who pays for the pilot and what must happen before a purchase order. A pilot that has no defined conversion criteria may demonstrate curiosity rather than demand.
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Use the DOE adoption lens
The U.S. Department of Energy’s Adoption Readiness Levels framework groups adoption risk into four buckets: value proposition, market acceptance, resource maturity and license to operate. It describes 17 dimensions that can be translated into a 1-to-9 score. Use the dimensions to expose a barrier—such as an unclear economic buyer, an immature supplier base or an unresolved permitting issue—rather than compressing the entire company into one number.
“Addressing technical challenges is necessary but not sufficient to successfully commercialize and scale a new technology.” — U.S. Department of Energy, Adoption Readiness Levels Framework
Check intellectual property and freedom to operate
Confirm who owns every asset required to build and sell the product: patents and applications, trade secrets, know-how, software, data, designs, biological materials and improvements. Trace institution-originated work through employment agreements, sponsored-research terms, grants, assignments and licenses. Check field-of-use, territory, sublicensing, milestone, royalty, diligence and termination obligations.
Separate protection from freedom to operate
A patent can support exclusion rights without giving the company permission to practice its own invention. Request a documented freedom-to-operate analysis for the intended product, geography and date, and identify opinions that depend on claim construction or untested assumptions. Map third-party components, standards, open-source software and data licenses as well as patent claims.
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Assess whether the advantage is durable. A patent count does not show enforceability, coverage of the commercial configuration or freedom from blocking rights. Conversely, a process protected only by unrecorded know-how may be vulnerable when employees or manufacturing partners change. The Deepsense science-and-technology diligence guide flags weak IP protection, freedom-to-operate concerns, insufficient team know-how and a better or cheaper competing technology as material risks.
Review regulation, quality and license to operate
Map requirements for the relevant geography and intended use before treating a demonstration as deployable. Depending on the sector, the path may include safety testing, environmental permits, clinical or product approvals, cybersecurity controls, quality systems, metrology, data protection, export controls, construction permits or customer-specific qualification.
Identify the authority, required evidence, sequence, fees, review time, appeal route and consequences of a failed test. Include rules that apply to installation and operation, not only to the product itself. A technically successful device can still be commercially blocked if a site cannot be permitted, an insurer will not underwrite it, or a customer’s quality system cannot accept its output.
Examine resources, supply chain and team execution
Resource and supply dependencies
- List critical materials, components, datasets, compute, facilities, specialist contractors and manufacturing or service partners.
- Record supplier qualification status, lead times, minimum order quantities, single-source exposure and substitution options.
- Check whether scale requires tooling, clean rooms, field technicians, hazardous-material handling or specialized logistics.
- Model working capital and inventory exposure when customers pay after delivery or qualification.
Team capability and concentration
Assess whether the team has the specialist skills needed to retire its most important risks: experimental design, systems engineering, manufacturing, quality, regulatory affairs, sales and deployment. Look for evidence of execution under constraints, not only credentials. Identify knowledge concentrated in one founder or external partner, succession plans and the time required to recruit missing skills.
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Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Compare readiness frameworks without conflating them
| Framework or lens | What it helps assess | Limit or caution |
|---|---|---|
| Technology Readiness Levels (TRL) | Technical maturity and the environment in which a technology has been validated or demonstrated. | Does not by itself establish adoption, economics, regulatory readiness or delivery capability. |
| DOE Adoption Readiness Levels (ARL) | Adoption barriers across value proposition, market acceptance, resource maturity and license to operate; 17 dimensions grouped into four buckets. | A single 1-to-9 score can conceal the specific barrier. Review dimension-level findings. |
| NITI Aayog Techno-Commercial Readiness and Market (TCRM) Matrix | Joint consideration of technology, commercialization and market readiness; its TRL, commercial-readiness and market-readiness scales are described from 1 to 9. | A structured framework, not a universal predictor. The report notes limitations and external variables that can affect ratings. |
Technical, commercial and market readiness can move at different speeds. Assess them separately, then document the gaps and dependencies. A company may have a validated prototype and an enthusiastic early adopter while lacking a qualified supplier, a permit or an economic model that supports a repeatable sale.
Build a risk register that drives decisions
A list of concerns is not a risk-management system. For every material risk, create one record with the fields below.
| Field | What to record |
|---|---|
| Claim or assumption | The precise condition that must be true, written so it can be falsified. |
| Current evidence | Source, test conditions, sample size, date, independence and known limitations. |
| Uncertainty and impact | What is unknown and how failure would affect performance, revenue, valuation, timing or required capital. |
| Decisive next test | The least expensive experiment, customer action, legal review or operational demonstration that could materially change the decision. |
| Owner | The person accountable for obtaining evidence and updating the record. |
| Cost and timing | Cash, people, facilities and calendar time required, including lead times. |
| Dependency | Preconditions, linked risks and the milestone that cannot proceed until this one is resolved. |
| Decision gate | The explicit continue, redesign, pause, partner, finance or stop decision that follows each result. |
Prioritize by consequence, not drama
Prioritize uncertainties whose failure would invalidate the company, materially reduce the achievable price or require substantially more capital. A technically difficult but non-critical optimization may rank below an unglamorous question about permitting or supplier qualification. Sequence the risk-burndown plan so that expensive commitments follow evidence that protects them.
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GAO’s guidance supports using readiness assessments to illuminate concerns and support realistic mitigation discussions before significant resource commitments. The purpose is not false precision; it is to make the next decision and its evidence visible.
A practical diligence workflow
- Frame the decision. State the instrument, amount, stage, customer, product boundary, geography and success criteria.
- Convert the pitch into claims. Write the performance, cost, adoption, IP, regulatory and financing assumptions as testable statements.
- Request the evidence ledger. Collect raw test data, protocols, failures, operating logs, customer documents, contracts, licenses, forecasts and approval correspondence.
- Map technical maturity. Classify each claim by environment and repeatability; use TRL language only with the underlying evidence.
- Challenge scale-up. Walk through materials, manufacturing or service delivery, integration, maintenance, quality and end-of-life conditions.
- Rebuild economics. Trace performance variables to cost and margin, then run downside sensitivities and identify the break-even drivers.
- Interview the buying system. Speak with users, budget owners, technical approvers and operators; document alternatives, timelines and conversion conditions.
- Review rights and permissions. Verify chain of title, licenses, freedom to operate, regulatory path, quality obligations and site constraints.
- Test execution capacity. Match each high-impact risk to a named owner, skill, supplier, facility and budget.
- Set gates and financing logic. Tie the next capital release to evidence that retires the most consequential uncertainty, not merely to elapsed time or a higher readiness label.
Common diligence traps and their corrections
| Trap | Correction |
|---|---|
| Treating a patent count, demo, lab result or TRL as proof of a scalable business. | Ask for operating-environment evidence, scale-up assumptions, economics, customer proof and delivery capability. |
| Calling market interest validated demand. | Name the user, buyer, budget, alternative, procurement path and paid-conversion condition. |
| Using one optimistic economic case. | Show sensitivities, downside cases and the test that would change each critical assumption. |
| Ignoring ownership, license terms or freedom to operate. | Trace chain of title and review third-party rights for the actual commercial configuration. |
| Underestimating manufacturing, supply, quality, regulatory, integration or financing dependencies. | Put each dependency in the risk register with cost, lead time, owner and a fallback. |
| Listing risks without action. | Attach a decisive test, milestone, resource requirement and decision gate. |
| Using readiness scores with false precision. | Show the evidence, uncertainty and dimension-level findings behind every score. |
What a decision-ready conclusion looks like
End diligence with a conditional map, not a technology adjective. State which claims are demonstrated, which are plausible but unproven, and which would change the investment case if they fail. Identify the next two or three gates, their owners, costs and dates, and the capital required to reach them. Specify what would cause a redesign, a partnership, a smaller pilot, a financing pause or a stop.
The resulting view should make clear whether the next commitment is buying information, building a repeatable product, qualifying a route to market or financing commercial deployment. That distinction prevents technical progress from being mistaken for commercial readiness and keeps capital tied to evidence.
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