Philippine AI startups spent 2023 and most of 2024 in survival mode, consolidating teams, extending runways, and waiting for the funding environment to normalize. By late 2025 and into 2026, deals have started moving again. Not at 2021 valuations, but moving.
The PH AI startup scene is small but focused. Most activity is in NLP for Filipino languages, AI-augmented BPO tools, and fintech underwriting. Consumer AI has seen less traction than enterprise B2B.
Who Is Raising
Senti AI
Senti AI is the most recognized name in Philippine AI. The company has been building Filipino-language NLP tools since 2018: sentiment analysis, text classification, and conversational AI that handles code-switching between English and Filipino better than any global model out of the box. Senti raised an institutional round in 2025 (terms undisclosed) and has expanded its client base to include government agencies, major banks, and telcos.
HealthNow PH
HealthNow PH raised a seed extension in Q1 2026 with participation from a Singapore-based health tech fund. The company connects patients to doctors, labs, and pharmacies through a mobile app, with an AI layer handling appointment routing and prescription follow-up. Healthcare is one of the most promising verticals for AI in the Philippines: large population, limited specialist access outside Metro Manila, and a telemedicine regulatory framework built during the pandemic.
Symph
Symph, the Cebu-based software studio, has been integrating AI tooling into enterprise product development for clients in healthcare, logistics, and retail. Not a pure AI company, but one of the technically sophisticated shops in the country and increasingly sought-after for AI integration work.
Most PH AI deals happening now are seed extensions or Series A bridge rounds, not fresh Series A. Investors are following up on existing bets rather than making new ones at scale. This is healthy but limits new entrant growth.
What Investors Are Funding
The investment thesis for PH AI in 2026 clusters around three areas:
- Filipino-language AI: Data and models that handle Tagalog, Bisaya, Ilocano, and English-Filipino code-switching. Global models are weak here. Local differentiation is real.
- BPO augmentation tools: The Philippine BPO sector employs ~1.5 million workers. AI tools that improve agent performance (quality assurance, assist, document extraction) have enormous addressable market and sophisticated local buyers.
- Fintech underwriting: Alternative data credit scoring has been active in PH fintech for years. New entrants are applying more sophisticated ML to the problem with better data pipelines.
The Funding Landscape
The primary investors active in PH AI:
| Investor | Type | Stage | PH Focus |
|---|---|---|---|
| Kickstart Ventures | CVC (Globe) | Seed–Series A | High |
| Foxmont Capital | Institutional VC | Seed | High |
| Insignia Ventures | Regional VC | Seed–Series B | Moderate |
| DOST grants | Government | Pre-seed | High |
| 1982 Ventures | Regional VC | Seed | Fintech focus |
DOST (Department of Science and Technology) continues to fund early-stage AI research through its programs, and the amounts are small by commercial standards but non-dilutive. Several 2026 funded startups used DOST grants to get to demo stage before raising from private investors.
What Remains Hard
GPU compute for training models is expensive for Philippine startups operating in pesos with peso-scale revenue. Most PH AI companies use APIs (OpenAI, Anthropic, Google) rather than training from scratch. Pragmatic, but limits long-term differentiation.
Filipino-language training data is scarce and expensive to annotate at the scale modern models require. ML engineers with production experience are in short supply. The university pipeline from DLSU, Ateneo, and UP is improving but thin relative to demand.
The most commercially viable path for most PH AI companies remains enterprise B2B: long sales cycles, but defensible contract value once won.
Frequently Asked Questions
Are there any PH AI companies that have raised Series A or later?
The disclosed funding landscape is limited. Senti AI has raised institutional rounds but doesn’t publicly disclose figures. Most PH AI companies at Series A equivalent are raising from regional Singapore-based funds or through strategic corporate investors rather than standalone VC.
What AI use cases are most commercially mature in the Philippines?
Fraud detection in fintech, credit scoring with alternative data, customer service automation for BPO clients, and document processing. Generative AI enterprise use cases are newer and still being validated at scale.
Is the Philippines good for AI research jobs?
For academic research, yes. DLSU, Ateneo, and UP have active NLP groups. For industry research engineering jobs with competitive pay, most PH-based ML engineers work remotely for US or Singapore companies. The domestic industry research job market is thin.