Evaluate a deep-tech startup as a chain of evidence, not as a compelling story. Start with the exact technical claim and independently reproducible data. Then test customer demand, intellectual-property ownership, regulatory obligations, manufacturing economics, team execution, runway and financing. If you are considering a job, apply the same business tests and add authority, equity, employment terms, intellectual-property assignment and personal safety.
Start with a written investment or career thesis
Before reviewing a pitch deck, write what would have to be true for the company to succeed. A useful thesis names the target customer, the measurable product advantage, the next value-creating milestone, the cash required to reach it and the evidence that would disprove the claim. This prevents a technically impressive demonstration from substituting for a viable business.
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Use a scorecard with these dimensions: technical evidence and maturity, risk reduction per quarter and dollar, customer proof, IP ownership and freedom to operate, regulatory and safety path, scale-up economics, team completeness, governance, runway, follow-on capital and exit options. A job candidate should also score personal learning, decision authority, compensation and downside.
| Dimension | Evidence to request | Failure that should change your decision |
|---|---|---|
| Technology | Raw data, protocols, calibration records, revision history and tests in the intended environment | Only a polished demo, unclear baselines or results that cannot be reproduced |
| Market | Named buyer, budget, paid pilots, renewals, procurement steps and competitive comparisons | Large theoretical TAM with no beachhead or purchasing evidence |
| IP | Patent families, assignments, licenses, open-source notices and freedom-to-operate analysis | Unclear ownership, university claims or a patent-count moat with no customer value |
| Scale-up | Pilot-line yield, cycle time, bill of materials, capex, working capital and supplier terms | Financial model assumes laboratory performance at production volume |
| Execution | Milestone owners, hiring plan, board records, reporting cadence and references | Pitch, financials and internal records contradict one another |
| Capital | Cash balance, monthly burn, committed financing, milestone cost and downside scenarios | The next milestone arrives after the cash is expected to run out |
Verify what the technology actually does
Turn the headline into a testable claim
Write the performance claim in one sentence with its conditions: output, accuracy, power, lifetime, throughput or cost; test temperature and environment; baseline or incumbent; sample size; measurement uncertainty; and failure modes. Ask for the raw data behind every chart, the test protocol, instrument calibration records, statistical treatment and the revision history of the prototype.
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Request demonstrations in the environment where customers will use the product. A benchtop result may not survive vibration, contamination, thermal cycling, network outages, operator variation or continuous operation. Ask which results were produced by the company, which were independently replicated, and whether negative experiments are recorded.
Use TRL correctly
The UK Knowledge Asset Management guide describes Technology Readiness Levels (TRLs) as a scale from basic research to operational use:
| TRL | Meaning |
|---|---|
| 1 | Observation of basic principles |
| 2 | Technology concept formulated |
| 3 | Proof of concept |
| 4 | Laboratory validation |
| 5 | Validation in a relevant environment |
| 6 | Model or prototype demonstrated in a relevant environment |
| 7 | Prototype demonstrated in an operational environment |
| 8 | System completed and qualified |
| 9 | Successful mission or operational use |
TRL is technical maturity, not commercial readiness. A high TRL does not prove that the company can manufacture repeatedly, meet quality and regulatory requirements, win customers or manage active IP. Ask the company to show the evidence supporting its claimed level and identify the specific evidence needed to reach the next one.
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Make two lists. The first contains questions about whether the underlying principle works at all: physics, chemistry, biological response, algorithmic validity or theoretical limits. The second contains engineering questions that arise even if the principle is sound: reliability, yield, thermal performance, integration, software controls, safety, supply chain and manufacturing repeatability.
Require a risk register with an owner, probability, consequence, threshold, experiment, due date and pass/fail criterion for every material uncertainty. Rank experiments by risk reduction per dollar and per quarter. The best next experiment is usually the one that retires a financing-critical uncertainty, not the one that produces the most impressive demo.
- Ask what observation would falsify the central claim.
- Check whether the proposed experiment isolates one variable or hides several assumptions.
- Compare laboratory data with prototype data and pilot-line data rather than accepting a single best result.
- Record dependencies: a sensor claim may depend on packaging, calibration, software and a particular supplier.
Prove customer pull instead of accepting market size
Identify the economic buyer
Ask who experiences the urgent problem, who uses the product, who signs the contract and which budget pays. Identify the incumbent being displaced, the measurable outcome that improves and the time required to reach value. A technically superior product can still fail if procurement, integration or certification takes longer than the customer’s planning cycle.
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Demand evidence beyond interest letters
Request customer references, paid-pilot contracts, acceptance criteria, renewal or repeat-order data, pipeline stages and procurement timelines. Distinguish a conversation, a non-binding letter, a paid pilot, a production purchase order and recurring revenue. Ask why a pilot did or did not convert and whether the customer would pay without grant support.
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Trace the IP chain of title and freedom to operate
Obtain the complete patent-family list, filing and grant status by jurisdiction, named inventors, assignment documents and licenses. Check whether founders, employees, universities, former employers or government-funded projects retain rights. Review confidentiality and trade-secret controls, open-source obligations, publication rights and any restrictions attached to sponsored research.
Ask for a freedom-to-operate opinion covering the product as actually planned, not merely the laboratory prototype. Determine which claims are enforceable, which jurisdictions matter and whether the company can afford prosecution and litigation. A patent count is not a moat if ownership is disputed, claims are narrow or competitors can design around them.
Map the defensibility that customers value: proprietary data, manufacturing know-how, a cost curve, regulatory approval, integration, customer lock-in or switching costs. The European Innovation Council describes technology diligence as examining protection, validity and investibility alongside market landscape, competition and positioning. Treat that work as a detailed review of evidence, not a ceremonial patent check.
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Map regulation, quality and safety before committing capital or labor
Identify the product classification and every authority, standard, test laboratory and quality-management requirement that applies in each target market. Include environmental permits, worker safety, cybersecurity, data protection, export controls and disposal obligations where relevant. Build a dated approval plan showing evidence required, cost, lead time and accountable owner.
A regulatory sandbox can provide a controlled setting for testing and standards work; it is not market authorization. India’s National Deep Tech Startup Policy Framework proposes sector-specific sandboxes and centralized compliance mechanisms, but eligibility and legal effect depend on the program and sector.
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For an investment, ask what approval failure does to the plan and whether the model includes testing, audits, quality staff and post-market obligations. For a job, ask who can stop a hazardous test, how incidents are reported, what training and insurance exist, and whether you would personally handle regulated materials or equipment.
Rebuild the scale-up and techno-economic model
Do not accept a financial model that multiplies laboratory output by a future factory. Recalculate unit economics from physical assumptions:
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- Cycle time, uptime, yield, scrap and rework
- Energy, labor, maintenance, tooling and quality inspection
- Capital equipment, facility costs and commissioning time
- Packaging, logistics, warranty, service and returns
- Inventory, supplier payment terms and working capital
Request pilot-line data and compare actual yield, throughput and failure rates with the assumptions in the board and investor models. Identify single-source components, minimum order quantities, qualification lead times, contract-manufacturing terms and tooling ownership. Calculate the cash needed to reach a bankable production process, not just the cash needed to build another prototype.
The European Investment Bank notes that deep-tech investors assess technology readiness and potential, scalability, expected future revenue, profit and cash flow, and exit opportunities. Manufacturing, service-delivery and quality risks remain even when the underlying technology has a high TRL.
Assess the team, governance and operating truth
Map each milestone to one accountable owner and test whether the team covers science, engineering, product, commercial, regulatory, manufacturing and finance. Review the hiring plan, advisor incentives, board composition, decision rights, reporting cadence, related-party transactions and succession coverage for critical roles.
Compare the pitch deck with financial statements, cap-table records, board minutes, customer evidence and team structure. GOV.UK investor-readiness guidance warns that investors “dig deep into the details”; unexplained differences between these records are a diligence red flag, not a presentation issue.
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Speak with current and former employees separately from founders. Ask how priorities changed after failed tests, whether bad news reaches the board, how decisions are documented and whether teams can stop work when safety or quality thresholds are breached. A founder who changes the plan when evidence changes is more valuable than one who protects an outdated narrative.
Connect milestones, runway and financing
Create a financing table that links each milestone to cost, timing, pass/fail metric, remaining runway and the next capital source.
| Milestone | What to specify |
|---|---|
| Technical proof | Test conditions, independent replication and falsification threshold |
| Pilot qualification | Yield, reliability, safety, quality and customer acceptance criteria |
| Regulatory submission | Classification, submission contents, review time, fees and owner |
| First revenue | Contract value, delivery date, gross margin and payment terms |
| Repeatability | Repeat orders, renewal rate, production variance and support burden |
| Scale | Capacity, capex, working capital, supplier resilience and financing source |
Stress-test delay, lower yield, slower sales, failed approval, a down round and the loss of a key supplier. Ask for current cash, monthly burn, committed financing and the date on which the company must raise again. A headline grant or national fund does not equal money available to this company; eligibility, geography, timing and co-investment conditions matter. For context, India’s Startup India Fund of Funds 2.0 was announced at ₹10,000 crore in 2026, but that figure is not a company-level commitment.
Consider the exit path as well as the next round. Who could acquire the technology, what strategic capability would they buy, and is there a credible route to public markets or sustainable cash generation? The EIC notes that technological diligence can inform commercial and technical milestones and investment structure and may be revisited after material changes or significant elapsed time. Treat diligence as a living process.
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Additional checks before joining as an employee
A job offer is an investment of time, reputation and income. Ask for the employment agreement and cap-table assumptions before accepting.
- Authority: Which decisions can you make without founder approval? What budget, equipment and people are assigned?
- Milestones: What must your role deliver before the next financing event, and what happens if that event is delayed?
- Equity: What is the option or share count, vesting schedule, cliff, strike price, exercise window, dilution assumption and treatment on termination?
- IP and publication: What inventions are assigned, what pre-existing work is excluded, and can you publish or continue academic work?
- Working conditions: What laboratory, field, travel, relocation, hazardous-material and safety-training obligations apply?
- Protection: What insurance, indemnity, sick leave, severance and workers’ compensation cover the role?
- Runway: How many months of cash remain under the current burn, and which milestone unlocks the next financing?
Speak with at least one person who left the company and ask for a specific example of a changed priority, a failed experiment and a resolved safety or quality concern. Refusal to provide basic employment terms or clarity about equity is itself decision-relevant evidence.
A practical diligence sequence
- Define the claim. Write the performance metric, conditions, baseline, uncertainty and failure modes.
- Inspect primary evidence. Review raw data, protocols, calibration, prototype revisions and independent replication.
- Map risks. Separate scientific uncertainty from engineering, regulatory, supply-chain and manufacturing risks; assign owners and dates.
- Interview customers. Verify the buyer, budget, paid work, conversion path, procurement cycle and measurable outcome.
- Trace rights. Confirm patent assignments, licenses, university or employer claims, open-source duties and freedom to operate.
- Rebuild economics. Test yield, cycle time, capex, working capital, warranty and supplier assumptions against pilot data.
- Audit execution. Compare the pitch with financial, governance and team records; interview current and former employees.
- Run downside cases. Model delays, failed approval, lower yield, slower sales, a down round and loss of a key supplier.
- Decide against pre-set gates. Invest, join, defer or walk away based on evidence and defined thresholds rather than enthusiasm.
Red flags that deserve a pause
- A claimed TRL is unsupported by tests in the relevant environment.
- Only best-case data is shown, with no uncertainty, failed runs or baseline comparison.
- Letters of interest are presented as revenue, or TAM is used without a reachable beachhead.
- Founders cannot produce assignment documents or explain university, employer or government rights.
- The model assumes production yield, price or margin without pilot-line evidence.
- One supplier, one scientist or one customer is critical and has no documented backup.
- Regulatory approval is treated as a date rather than a sequence of evidence and review steps.
- Financial, governance and team records do not match the pitch.
- The company cannot state current cash, burn, next milestone cost or financing trigger.
- Employees lack authority to stop unsafe work or are asked to accept broad IP and liability terms without explanation.
How to make the final decision
Proceed when the company can connect reproducible technical evidence to a defined buyer, owned and usable IP, a credible approval path, manufacturable economics, accountable execution and enough capital to reach the next proof point. Defer when one uncertainty is material but measurable and the company has a funded experiment with a clear decision date. Walk away when evidence is inaccessible, ownership is unclear, the market case depends on uncommitted interest or the company cannot fund the next milestone.
For a job, accept only when the role’s authority, safety, compensation and equity are explicit and the company has a realistic path to finance the work through its next milestone. Deep-tech outcomes are rarely determined by the scientific idea alone; they are determined by whether every link from science to cash survives independent checking.
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Frequently Asked Questions
What is the most important document to request first?
Request the evidence package for the central technical claim: raw test data, protocols, calibration records, baseline comparison, uncertainty and prototype revision history. It reveals whether later market and financial claims rest on a reproducible result.
Does a high TRL make a deep-tech startup investable?
No. TRL describes technical maturity. It does not establish manufacturing capability, regulatory compliance, customer adoption, unit economics or follow-on financing.
How can I verify that a startup really owns its invention?
Review patent-family records, inventor assignments, employment and university agreements, licenses, sponsored-research terms, open-source obligations and any freedom-to-operate opinion for the planned product.
What should I ask about runway before joining?
Ask for current cash, monthly burn, committed financing, the cost and timing of the next milestone, and the condition that unlocks the next round. Test the answer against downside cases such as delay or lower yield.
Are letters of intent proof of customer demand?
Usually not. Separate non-binding interest from paid pilots, production purchase orders, renewals and repeat revenue, and verify the buyer, budget, procurement process and conversion criteria directly with customers.
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