Predikta · Final Investor Deck · Seed Round US$1.5M

01 · The Problem

Brands launch blind. Research arrives too late.

Campaign decisions happen weekly. Traditional research takes 3–8 weeks and costs ₱100K–2M+ per study. By the time insight arrives, the budget is already spent.

Why Now

USD 4.64B PH digital ad spend in 2026 — growing +10.2% CAGR

92% of PH organizations using AI — but none simulate audience psychology

Gen AI created ad creative abundance — now brands need to know what works before spending

Zero culturally-calibrated Filipino behavioral AI tools exist at commercial scale

3–8 weeks

Research cycles can't keep up with campaign cadence

Brand and agency teams iterate messaging weekly — sometimes daily. Traditional research takes 3–8 weeks. By the time results arrive, the brief has changed and the insight is answering the wrong question.

₱100K–2M+

Testing every concept is economically impossible

A single market research study in the Philippines can run from ₱100K to ₱2M+. Most brands afford one or two per year — so the majority of campaign concepts go to market untested. Predikta is designed to reduce this to less than 10% of traditional cost.

Generic AI

Global AI tools produce generic Filipino insight

Western psychographic models don't encode collectivism, family purchase influence, bayanihan values, or religiosity as a decision driver. Generic LLM prompts produce generic output — useless for brands needing culturally specific insight.

No tools

Analytics tell you what failed — after you've already failed

Most marketing tools are retrospective. They explain performance after budget is spent. There are almost no tools built to answer the only question that matters before launch: how will this audience actually respond?

02 · The Product

Simulate your audience. Before you launch.

Predikta builds psychographic models of Filipino consumer segments and runs behavioral simulations against campaign inputs — results in hours, no fieldwork, no sample bias.

Behavioral simulation platform built on 68.9M+ Filipino psychographic profiles — derived from a 2,485-respondent nationally representative survey co-developed with UP Los Baños (Statistics) and UP Diliman (Psychology)

95% trait alignment · 88% national-level sentiment simulation accuracy — supported under academic preprint study conditions. Available as an arXiv preprint: arXiv 2505.22125v1. The 200+ campaign commercial validation study currently underway will test real-world prediction accuracy separately.

Grounded in HEXACO, Schwartz Values Theory, and System Justification Theory — recalibrated for Filipino cultural psychology at the model level, not through prompt engineering. Collectivism, religiosity, and bayanihan are structural, not bolted on.

Campaign intelligence in minutes, at less than 10% the cost of traditional research. Know how your audience will respond before a single peso is spent.

Powered by Google Cloud, AWS, and Azure — enterprise-grade infrastructure from day one, built for Southeast Asia scale.

Behavioral Model →

Step 01

Submit campaign concept

Upload a brief, creative direction, copy variants, or a concept deck in any format.

Step 02

Select target segment

Choose from pre-built Filipino psychographic profiles or configure a custom segment.

Step 03

Run behavioral simulation

Predikta runs thousands of simulated responses calibrated against 68.9M profiled Filipinos.

Step 04

Receive actionable insight

Predicted sentiment, segment breakdowns, and message refinement recommendations — in minutes.

What the client gets in minutes

A Predikta-style campaign simulation output comparing two campaign concepts across a defined Filipino consumer segment.

P Predikta Campaign Simulation

Client: GlutaMAX

Segment B: Urban Female, 25-34

Run time: 06m 42s

Workflow

Audience

Campaign Test

Sentiment

Emotions

Recommendations

Outputs

Executive Summary

Segment Detail

Campaign Concept Test: Glow Platform

Comparing emotional response, intent-to-share, and message risk across two concepts.

Variant A wins

Recommended

Variant A: “Glow From Within”

8.4

Positive sentiment78%

Intent to share71%

Trust signal64%

Lower performance

Variant B: “Science of Beauty”

5.9

Positive sentiment41%

Intent to share32%

Confusion risk44%

Recommended action: Lead with “Glow From Within,” but add a mass-market value cue to reduce price-sensitivity risk among conformity-value clusters.

Dominant emotions

Aspiration 68%

Trust 21%

Skepticism 9%

Segment response

Benevolence + AchievementHigh fit

Security valuesMedium fit

Price-sensitive clusterRisk

Confidence note

Illustrative product output. Predikta scores are directional simulation outputs from behavioral profiles, validated against real campaign outcomes. They are not guarantees of in-market performance.

Recommended

Variant A: “Glow From Within”

8.4 / 10

Dominant emotion: Aspiration (68%) + Trust (21%)

Segment response: 78% positive intent-to-share. Resonates with Benevolence + Achievement values cluster.

Top risk flag: Price-sensitive consumers may perceive the claim as aspirationally exclusive.

Recommendation: Pair aspirational message with accessible pricing/value framing.

Lower Performance

Variant B: “Science of Beauty”

5.9 / 10

Dominant emotion: Confusion (44%) + Skepticism (29%)

Segment response: 41% positive. Technical framing misaligns with Universalism and Security values cluster.

Recommendation: Simplify language and shift from technical proof to emotional relevance.

Confidence note: Predikta scores are directional simulation outputs from 68.9M behavioral profiles, validated against real campaign outcomes. They are not guarantees of in-market performance.

03 · Scientific Foundation & Commercial Signal

Not prompt engineering. A calibrated instrument.

Predikta's behavioral model integrates HEXACO and Schwartz Values Theory — culturally recalibrated for Filipino psychology. Collectivism, family decision-making, and religiosity are not parameters you can add to a prompt.

95%

Trait Alignment — psychographic model matches real human profiles across all measured personality dimensions under preprint study conditions

88%

National-level sentiment simulation accuracy — consumer sentiment simulation vs. real survey outcomes across 12 consumer scenarios

arXiv

2505.22125v1 — co-authored with University of the Philippines (UP Los Baños & UP Diliman)

The arXiv preprint reports psychographic modeling replicated survey-style sentiment with 88% national-level accuracy under study conditions. This is evidence of survey-alignment, not definitive proof of real-world campaign prediction. The 200+ campaign commercial validation study currently underway is designed to assess that separately. These are distinct questions, and we keep them distinct.

Validation Stack — Ordered by Evidence Strength

1

Academic Preprint — arXiv 2505.22125v1

Co-authored with University of the Philippines (UP Los Baños & UP Diliman). Reports 95% trait alignment and 88% survey-level sentiment accuracy under study conditions. Not peer-reviewed — but a credentialed academic foundation.

Published

2

Fintech Soft-Launch — 72% → 75% sentiment alignment

Predikta predicted 72% positive campaign response before launch. Client follow-up survey returned 75%. A 3-point delta. Two additional comparisons showed consistent directional alignment. n=3 — early indicator, not conclusion.

Live signal

3

AdSpark Commercial Backtest — 200 deployed ads, r=0.52

April 2026 backtest against 200 deployed AdSpark campaigns showed meaningful correlation with actual campaign outcomes. Ranking capability validated across a real agency dataset. Directional commercial signal — not an in-market guarantee.

Underway

4

200+ Campaign Formal Validation Study — currently underway

The first broader commercial test designed to assess whether Predikta's simulation outputs align with observed real-world campaign performance. Results will be the primary evidence for the Series A narrative.

In progress

Detailed Commercial Signals

Early Commercial Signal — Fintech Soft Launch

72%

→

75%

Δ 3 pts

In a consumer finance soft-launch pilot, Predikta predicted 72% positive campaign response before the campaign ran. The client's follow-up survey returned 75% positive. Three percentage points delta. Two additional comparisons have shown consistent directional alignment.

n=3 commercial comparisons during soft launch. Directionally consistent with preprint findings. The currently underway 200+ campaign validation study is the first broader commercial test — this remains an early indicator, not a conclusion.

Home Credit Philippines — Retrospective Validation

Watch case study video →

Predikta was used during soft launch to assess historical campaign data from Home Credit's rich product portfolio. By stress-testing Predikta against past campaign data, the work provided early directional evidence that simulation outputs may align with observed market performance.

Enterprise workflow active · Stage 2 in progress. A real enterprise validation workflow — not a demo.

AdSpark Commercial Backtesting — 200 Deployed Ads

r = 0.52

correlation to campaign outcomes

In April 2026, Predikta signals were backtested against 200 deployed AdSpark ads. The analysis showed meaningful correlation with actual campaign outcomes, with ranking capability validated and cost implications projected.

Scope note: April 2026 AdSpark backtest across 200 deployed ads. Directional commercial signal only; not a guarantee of in-market performance. Include the exact r-value only after investor-distribution approval.

Commercial backtesting is directional. It strengthens the validation stack but does not guarantee future in-market performance.

Watch the Predikta demo on YouTube

Watch video on YouTube →

04 · Traction

Soft launch. Already paying.

Commercial activity began March 2026 as a controlled soft launch — before any scaled commercial outreach. v4 tracking shows 7 active clients in the soft-launch cohort, named paying/recurring accounts, and active enterprise pilots moving toward conversion. Full GTM launch is next.

7

Active clients — soft launch cohort

5

Active enterprise pilots — in active conversion discussions

30+

Product testers — soft launch cohort

105+

Pipeline accounts — full GTM not started

Context: soft launch only — full GTM has not started. Zero dedicated sales team. Zero marketing spend. Zero scaled outreach.

Paying

Thynker Tech · Unbox Philippines · GlutaMAX · BEVI · Riot Games · iPeople / Mapua

Repeat simulations → recurring workflows

Active Pilots

Home Credit · Globe · AdSpark · Inquiro · AsiaLink

In active conversion discussions

Pipeline

Century Pacific · 7-Eleven · L'Oreal · OPPO · BYD · AXA · DDB · Havas · Acer · Ripple8 · Cyberzone · Mapua · Unilab

Warm, named conversations

One-time pilots don't build a business. Workflow replacement does. When full commercial launch begins, we will be scaling a workflow that has already shown early stickiness — not discovering whether one exists.

05 · Market & Revenue

Early mover in validated localized behavioral simulation.

Predikta sits at the intersection of marketing technology, consumer insights, synthetic data, and decision intelligence. The Philippines is the pressure-test market. Southeast Asia is the prize.

Philippine Market Sizing

TAM — PH marketing, advertising, research	21,600 firms
SAM — AI-ready + research budget capacity	6,609 firms · ~₱2.4B annual opportunity
SOM Year 5 base	330 clients
Average monthly subscription	₱45K/month
Philippines SOM Year 5 ARR	~₱206M ARR
PH digital ad spend (2026E)	USD 4.64B
Digital ad CAGR through 2030	+10.2%
PH AI market CAGR through 2030	+41.5%
PH organizations using AI in some capacity	92%

SEA Market Expansion

If validated at commercial scale, the Philippine wedge expands into a larger Southeast Asia opportunity: approximately 122,100 firms across Indonesia, Thailand, Malaysia, Singapore, Vietnam, and the Philippines with active advertising budgets and capacity for Predikta.

Pricing — Monthly Subscription + Top-up

₱15K

Tier 1

₱45K

Tier 2

₱90K

Tier 3

₱90K/mo

Bespoke + ₱1.2M+ pathway fee

Gross margins: 80% text-only · 75% text+image · 70% blended standard · 50% bespoke pathway · Top-up credits available

5-Year Revenue — Base Case (PHP)

Year	Revenue	Gross Profit	GM%	Clients
2026	₱12.5M	₱9.4M	75%	34
2027	₱63.7M	₱46.9M	74%	111+
2028	₱152.1M	₱115.8M	76%	203+
2029	₱271.1M	₱210.7M	78%	307+
2030	₱379.8M	₱295.2M	78%	415+

Conservative (PHP) track · Break-even path contingent on fundraise close

2026

₱12.5M

2027

₱63.7M

2028

₱152.1M

2029

₱271.1M

2030

₱379.8M

06 · Why This Gets Harder to Copy

Three defensibility pillars — and widening.

We're building three compounding advantages — data flywheel, localization infrastructure, and strategic distribution — each of which gets stronger with usage, validation, and partner-led market access.

01 · Data Flywheel

Accuracy compounds with every validated simulation

Every simulation can be compared against observed outcomes. More usage creates more validation data; more validation data improves calibration; better calibration improves customer trust and repeat usage.

In progress · 200+ campaign validation study

02 · Localization Infrastructure

68.9M Filipino representative profiles

Built from nationally representative respondents via University of the Philippines and scaled through census integration. Cultural psychology is structural in the model — not bolted on through prompts. The same formula can be replicated market-by-market across SEA.

Philippines complete · SEA replication planned

03 · Strategic Distribution

Enterprise access through the Globe / Brave ecosystem

Selected for the 917Ventures Velocity Program and in partnership with Globe Telecom & Brave Connective. The ecosystem creates access to enterprise buyers and validation partners; Predikta still must convert that access into repeatable revenue.

Strategic ecosystem · not yet scaled revenue

Competitive Landscape — How Predikta Positions

Capability	Predikta	Generic LLMs (GPT-4 etc)	Traditional Research	Global MR Platforms
Filipino psychographic profiles	✓ 68.9M profiles	✗ Generic	✗ Manual	✗ Not localized
Pre-launch campaign scoring	✓ Minutes	~ Hallucination risk	✗ Weeks/months	~ Slow + expensive
Behavioral science foundation	✓ HEXACO + Schwartz	✗ None	~ Varies	~ Generic frameworks
Cost vs. traditional research	✓ <10% of cost	~ Low cost, low trust	✗ High cost	✗ High cost
Academic validation	✓ arXiv + UP collab	✗ None	~ Peer-reviewed methods	~ Proprietary
SEA replication path	✓ By-country model	✗ Not localized	✗ Expensive	~ Limited

Three Falsifiable Conditions for Venture-Scale Outcomes

We're not asking investors to believe in inevitability. We're asking them to back three specific falsifiable hypotheses — each testable within this raise cycle.

1

Simulation must align with real-world campaign outcomes — not just survey sentiment

The 200+ campaign validation program currently underway will be the first externally assessed test of commercial prediction accuracy. The 72% → 75% fintech soft-launch result gives us an early directional signal, but the broader study is designed to test whether that pattern holds at scale. If it does, this becomes a commercially defensible prediction engine. If it doesn't, we'll know before the next raise, and the category thesis weakens accordingly.

Currently underway · 200+ campaign validation study

2

Customers must use Predikta repeatedly — not just experimentally

Named paying and active soft-launch accounts have already shown repeat usage. Scaling toward 34 active clients by EoY 2026 while maintaining that repeat-use pattern is the key commercial milestone of this raise. One-time pilots don't build a business. Workflow replacement does.

Early signal positive · repeat usage observed

3

Localized models must outperform generic AI tools on Filipino consumer insight

If culturally-calibrated Philippine models consistently produce better predictions than generic LLM prompting, the localization investment creates defensible product value. If accuracy converges, the moat weakens. The preprint suggests localization matters significantly. Commercial measurement is underway.

Preprint-supported · Commercial measurement underway

07 · Leadership

The unusual combination this category demands.

Building behavioral decision infrastructure requires enterprise execution, behavioral science depth, and the credibility to attract academic collaborators and enterprise ecosystem partners simultaneously. This team has all three — and has done it before.

Netopia AI

Behavioral AI company

Map human behavior using behavioral science and AI to understand, simulate, and predict behavior at scale.

Singapore · Philippines · 2026

2 Co-Founders
6 R&D behavioral scientists and data scientists
5 product team members across AI, engineering, and software
Commercial, marketing, product, and management advisors

AK

Axel Kornerup, MPA

CEO & Co-Founder

Built and sold netopia — the Philippines' largest internet café network. Part of the founding team at InterVenn Biosciences (AI liquid biopsy, $100M+ raised from Softbank, Genoa, Xeraya). Founded four prior ventures across internet infrastructure, telco, gaming, and clean energy. University of the Philippines MPA. 26 years building companies in markets where infrastructure is the product.

netopia — acquiredInterVenn $100M+4 prior venturesUP MPA

JA

Jason Albia, MS

CSO / CTO & Co-Founder

Computational scientist with 40+ academic papers and approximately $4M in AI R&D funding secured. Co-designed Predikta’s psychographic simulation architecture, the framework behind the arXiv preprint reporting 95% trait alignment and 88% survey-alignment accuracy. His work sits at the intersection of computational science, behavioral science, and AI systems design.

40+ papers~$4M R&DarXiv co-authorComputational Science

Aldo Carrascoso

InterVenn Biosciences · $1B+ outcomes

Fundraising · US expansion strategy · Deep enterprise commercialization track record across biotech and technology.

Jojo Flores

Plug and Play Ventures · $10B+ portfolio

Enterprise BD · VC introductions · Global startup ecosystem access across SEA and Silicon Valley.

Jane Walker

ex-PLDT / Singtel / San Miguel

SEA partnerships · Enterprise marketing · Veteran marketer with deep regional network and brand-building track record.

40+

Combined years in AI

80+

Combined years in marketing research

40+

Combined years in data science

$1.5B+

Combined market value generated from past ventures

Full Team →

Validation & Press

In the news. In the ecosystem. In the market.

Third-party validation across press, academic research, and enterprise partnerships.

Article · Globe Newsroom

Globe Advances Enterprise Innovation as Netopia AI Joins 917Ventures' Velocity Program

Read full article →

Academic Preprint · arXiv 2505.22125v1

Sentiment Simulation using Generative AI Agents — co-authored with UP Los Baños & UP Diliman

Read the paper →

Case Study · Home Credit Philippines

Predikta Partners with Home Credit — simulation compared against real historical campaign performance data

Watch video →

08 · The Ask

Raising to ignite full commercial launch.

Netopia AI is seeking financial co-investors for a US$1.5M Seed Round to scale Predikta's Philippines go-to-market rollout. Selected for the 917Ventures Velocity Program and in partnership with Globe Telecom & Brave Connective, this round has one commercial job: prove the first wedge is a repeatable, venture-scale business within approximately 12 months of runway.

Use of Funds

35% Sales & Customer Success — scaled GTM, outbound sales motion, 2 AEs + 1 customer success hire

30% Product & Engineering — client data integration, multimodal inputs, FGD capabilities

20% Dataset Enrichment — scale audience, operationalize retraining, build replication gap

15% Validation & Operations — 200+ campaign validation study and operational infrastructure

Milestones This Round Funds

~12 months runway to execute full commercial launch and transition from soft launch to full GTM

34 active clients by EoY 2026 and ₱12.5M 2026 revenue target

Convert Globe, AdSpark, Inquiro, and Home Credit pilots into paid recurring workflows

Complete and release the 200+ campaign commercial validation study — the first broader test of real-world prediction accuracy

Build the Series A case: PH product-market fit, repeatable enterprise GTM, and initial ASEAN licensing revenue

Deal Summary

Round Size

US$1.5M Seed

Terms

Available on Request

Accelerator

917Ventures Velocity

Runway Target

~12 months post-close

Interested in Co-Investing?

Predikta is raising a US$1.5M Seed Round. We're inviting financial co-investors who understand the Southeast Asia behavioral intelligence opportunity. Reach out directly to start the conversation.

Email Axel → axel@netopia.ai Email Jason → jason@netopia.ai Request a Demo

09 · Exit Optionality

Built for strategic exit optionality.

Predikta is being built as the localized behavioral intelligence layer for Southeast Asia. If the company proves repeatable ROI improvement in the Philippines and replicates across ASEAN, likely strategic acquirers include market research platforms, agency holding companies, adtech and CRM platforms, and regional telco data and AI businesses seeking proprietary SEA behavioral datasets.

01

Strategic buyer categories

Market research platforms, agency holding companies, adtech and CRM platforms, and regional telco data/AI businesses that need localized behavioral simulation infrastructure.

02

Series A target milestone

PH product-market fit, repeatable enterprise GTM, and initial ASEAN licensing revenue.

03

Likely exit path

M&A is the most probable exit pathway given the localization moat and validated behavioral dataset — a layer that global platforms cannot easily replicate.

Know how your audiencewill respond before youspend a peso.