10-minute speaker script built for clarity first

0:00-0:45 · Segment 1 · Deck Slide 1

Clear definition in two lines

Say: "BioPath turns one farm map into optimized trap coordinates with measurable uplift, so placement becomes evidence-based instead of guesswork."

Say: "Commercially, we start with a paid pilot and convert to annual decision-support subscription, so value is tied to repeatable operations rather than one-time consulting."

Say: "The practical distinction for this panel is simple: we do not stop at visualization. We output decisions, metrics, and artifacts that another reviewer can rerun and verify."

Say: "At this first slide, remember the contract rather than the math: same input, repeatable output, and a measurable uplift claim."

Transition: "I will now make this concrete with one short scene before any algorithm detail."

Recovery: "Map in, traps out, proof attached."

0:45-1:35 · Segment 2 · Deck Slide 2

Problem and customer pain

Say: "In complex farmyards, manual trap placement depends heavily on individual experience. That leads to variability between technicians and blind spots around feed routes, storage edges, and access chokepoints."

Say: "Our primary customers are farm operations teams and pest-control operators. Secondary stakeholders are managers and compliance reviewers who need an auditable reason for every trap move."

Say: "The hidden operational cost is repeated re-positioning, fragmented records, and weak handover across shifts. Teams spend time arguing about placement instead of improving outcomes."

Say: "If we solve this well, we reduce biological risk and organizational friction together, because decisions move from personal intuition to shared evidence."

Transition: "Next, I will show exactly how we convert real context into transparent computation."

Recovery: "Short version: high variability, low auditability, repeated rework."

1:35-2:25 · Segment 3 · Deck Slide 3

Source -> model -> solve conversion

Say: "We use public farmyard imagery only as context. Optimization is run on synthetic geometry and a photo-informed prior, so every computational assumption is explicit and reproducible."

Say: "This boundary matters: real-world context gives interpretability, while synthetic geometry gives stability and auditability. We never claim hidden private telemetry in this demo."

Say: "The user workflow is concise: upload layout, set trap budget, run solve, run benchmark, then export one run artifact package. That package is what makes technical review fast."

Say: "Because inputs and outputs are explicit in JSON plus metrics, another person can rerun the same pipeline and check if the same claim still holds."

Say: "This also supports long-term use: whenever site structure changes, we update the structured map layer and keep a clear version history for comparison."

Transition: "Now I will explain the technical edge in plain language."

Recovery: "Transparent conversion is why this is science-backed and operationally usable."

2:25-3:15 · Segment 4 · Deck Slide 4

Technical originality and robust score

Say: "Our core is scenario-robust decision making under uncertainty, not static rule heuristics. We model movement uncertainty explicitly and validate under Monte Carlo scenario variation."

Say: "Robust score means conservative capture under uncertainty scenarios, using the worst scenario as the headline score, not a best-case number."

Say: "Our primary comparator is a practical heuristic baseline with edge and spacing rules. So our uplift claim is tested against a realistic operator baseline, not only against pure random placement."

Say: "This is where my stochastic-process PhD work connects directly to product value: uncertainty is inside the decision objective, not a post-hoc disclaimer."

Say: "Technically this gives product defensibility too: performance improves through calibrated uncertainty and benchmark loops, not through fixed hard-coded placement tricks."

Transition: "With method clarified, I will now show one fixed proof contract."

Recovery: "Uncertainty-aware, comparator-explicit, reproducible."

3:15-4:15 · Segment 5 · Deck Slide 5

Proof contract with explicit comparator

Say: "With k equals 6 traps, optimized capture is 59.3 percent. Heuristic baseline is 40.7 percent, so uplift is plus 45.6 percent under the same trap budget."

Say: "Robust capture is 38.6 percent, validated with Monte Carlo N equals 140. So this is not one lucky run; it is a conservative score under uncertainty."

Say: "Random baseline is 34.1 percent and gives plus 74.0 percent uplift, but for realism we report heuristic as primary and random as secondary."

Say: "This gives a concise proof contract you can remember: optimized, baseline, uplift, robust, and MC runs. If those five are present, the claim is complete."

Say: "When judges ask for confidence, I point to this structure: we are not asking trust in a black box; we are showing a measured decision cycle."

Transition: "Now I will connect proof to market size and pricing logic."

Recovery: "Same budget, explicit comparator, conservative robustness."

4:15-5:20 · Segment 6 · Deck Slide 6

Market, pricing, and growth potential

Say: "We do not start from the full UK farm count as a sales fantasy. We start from the payable segment: high-output farms in England, around fifteen thousand in public statistics."

Say: "That segment is only about sixteen percent of farm businesses but contributes most output, so budget and governance demand are stronger for decision-support tools."

Say: "Our pricing is five thousand pounds for an eight-week pilot and nine thousand pounds per site per year for subscription, with a thirty-five percent pilot-to-subscription assumption."

Say: "Operationally, if the workflow saves even one technician day per month on re-positioning, handover, and audit reporting, subscription economics are already defensible."

Say: "At one percent penetration of this SAM, ARR is about 1.35 million pounds. Our realistic three-to-five-year SOM target is thirty to seventy sites, around 270k to 630k ARR."

Say: "For route-to-market, we combine direct farm pilots with pest-control operator channels, so one successful operator relationship can scale across multiple sites."

Say: "This gives an investable balance of ambition and realism: clear market headroom, but near-term growth assumptions that are operationally deliverable by a focused founder-led team."

Transition: "I will now show the finance discipline behind this growth path."

Recovery: "Bottom-up model first: customers times price times conversion."

5:20-6:15 · Segment 7 · Deck Slide 7

Finance and funding path

Say: "Our year-one cash cost baseline is twenty-eight thousand pounds, covering cloud, pilot execution, and essential delivery operations. Founder build time is in-kind at this stage."

Say: "Funding route is explicit and current: we are applying through CREGS plus LINCAM PoC. Official Ceres pages list a five-to-twenty-thousand-pound range with a seven-minute pitch format."

Say: "Use-of-funds is milestone-linked: pilot evidence generation, product reliability upgrades, and conversion-ready reporting assets. Money in directly maps to measurable outputs."

Say: "This is a conservative staging strategy: prove repeatable uplift and conversion readiness first, then scale only after recurring contract signals are visible."

Say: "If challenged on the 28k baseline, clarify the boundary immediately: this is year-one cash operating cost, while founder build time is in-kind in this phase."

Transition: "Now I will run a two-minute live demo path."

Recovery: "Finance is milestone-linked, not headcount-led."

6:15-8:15 · Segment 8 · Live demo in Pitch Studio

Two-minute live demo path

Say while clicking: "First, run solve to generate optimized coordinates. Second, run benchmark to compare optimized decisions against heuristic baseline under the same trap budget."

Say: "Now read the proof contract from the panel: optimized capture, baseline, uplift, robust score, and Monte Carlo run count. This is the same contract shown in the deck."

Say: "If API is unavailable, Pitch Safe mode keeps curated evidence visible, so the narrative remains stable and no audience time is wasted on technical recovery."

Say: "Notice we separate capture from robust score, and mean distance from weighted mean distance. Weighted mean reflects photo-informed risk priorities, so it can differ from plain mean."

Say: "The value here is not animation. The value is that every decision and number is traceable, comparable, and reproducible in another run."

Say: "For time discipline, I read one complete proof sentence live and then stop. Extra technical detail is reserved for Q&A."

Transition: "I will close with team fit and explicit ask."

Recovery: "If timing is tight, read the proof line once and move to ask."

中文提示：这段只读“优化、基线、提升、稳健、MC”，别展开算法细节。

8:15-9:30 · Segment 9 · Deck Slide 8

Team credibility and explicit ask

Say: "I am Xiaoxiao Zhouyi, Founder and Sole Builder, and a PhD Candidate in stochastic processes. I built this stack end to end, from solver and API to benchmark and pitch interface."

Say: "Our ask is concrete: two pilot introductions, one practical eight-week trial site, and one support letter for a five-to-twenty-thousand-pound LINCAM PoC application."

Say: "Expected return is explicit: repeatable uplift evidence, first pilot-to-subscription conversion, and a funding-ready package for controlled expansion."

Say: "Support now buys measurable milestones, not vague ambition. If any assumption fails, we report the miss and adjust transparently using the same proof standard."

Say: "This is the trust contract from my side: clear assumptions, visible metrics, explicit asks, and accountability on outcomes instead of storytelling alone."

Transition: "One final sentence, then questions."

Recovery: "We are asking for practical pilot support that converts measurable proof into recurring revenue."

9:30-10:00 · Segment 10 · Close + Q&A bridge

Close clearly and stop

Say: "BioPath converts one farm map into measurable trap decisions with transparent proof, realistic pricing, and milestone-linked finance. I am happy to go deeper on model assumptions, pricing sensitivity, or pilot rollout details."

Action: Pause. Invite questions.

Deliver confidence, then let the panel speak.