AI that ships.
An AI company in the Philippines. Mobile apps and on-device AI, web apps and real-time platforms, AI integration and automation, AI adoption consulting, and WordPress development. Everything below was built in-house, end to end.
No signup, no call. The only two things here you can use before you talk to Zedlav.
The proof
Five things Zedlav built. Nothing here is a mockup.
AllerMoi
A Philippine allergy tracker with on-device AI. Log a flare-up in under thirty seconds, and the app finds the patterns across symptoms, food, medication, and the weather. Everything stays on the phone.
Free disaster tracker covering earthquakes, typhoons, volcanoes, wildfires, floods, and storms across the Philippines. Aggregates USGS, NASA, PAGASA, GDACS, and Open-Meteo into a severity-scored feed on Cloudflare Workers with zero server costs.
Korda tells you whether the person you are with is still with you. Not where they are. There is no map, no coordinate, and no server holding a history of either.
Move records between the platforms a business already runs on. The model proposes the field mapping, a person approves it, and a dry run happens before anything is written.
One audit across eight dimensions, from meta and schema to Core Web Vitals and how AI search engines describe you. Scored, ranked by impact, delivered as a document.
The stack wasn’t bought. It was built in-house.
Client work runs on an AI operations engine Zedlav engineered and runs in-house: persistent memory, mechanical enforcement gates, and automation across platforms clients already live in. It is hardened by incidents, not by speculation.
Nothing gets re-explained
Project knowledge persists between sessions, so context that was established once stays established.
Gates, not vibes
Pre-flight hooks block dangerous operations before they run. Anti-fabrication and citation rules are enforced in code and covered by an automated test suite.
Priced to run repeatedly
The engine is engineered so the cost of running it does not scale with the size of the problem. That is what makes recurring sweeps and repeated passes affordable rather than a line item.
Hands on the tools
Real browser sessions and Android devices driven directly, for the work that has no clean API waiting for it.
Drift detection
Client stacks are trained to a baseline and watched for drift across CRM, CMS, analytics, and email, so problems surface as advisory instead of outage.
Scoped by tenant
A gated gateway lets clients use the engine inside a sandboxed workspace, without exposure to anyone else’s data.
Human-in-the-loop is not a limitation. It is the architecture.
Every high-blast-radius decision requires explicit human approval. AI handles execution and verification at volume. The team makes every decision that matters. That is an engineering position on how reliable these models actually are, not a promise waiting to be broken.
AI makes mistakes. Zedlav’s get caught first.
Anyone can point a good model at your problem. What decides whether the output is safe to hand you is the layer around it. Every gate below refuses to run rather than warn, each one traces to a dated failure in Zedlav’s own work, and the whole layer is covered by an automated test suite so it cannot quietly degrade.
Deliverables are checked before they leave
Every file that reaches you is verified for accuracy and for material that belongs to another engagement. Not reviewed when someone remembers. Checked as a condition of release.
Work lands where it was scoped to land
A deploy to an environment outside the agreed scope does not happen. There is no confirmation prompt to click through at the end of a long day.
The number in the report is the number that was there
An unsourced claim cannot reach a deliverable. This is a property of the pipeline, not a habit.
One engagement cannot reach another
Client material is isolated by construction. Not by a policy someone is trusted to remember.
| Model access | Client work runs on paid enterprise-tier model APIs under commercial terms, never on consumer accounts. |
|---|---|
| Credentials | Your credentials sit in encrypted storage, or in your own systems where the platform supports it. |
| Shared knowledge | Shared knowledge holds platform patterns, never client material. |
| Deliverables | Checked for cross-engagement material before they reach you. |
What Zedlav does for you
Mobile Apps and On-Device AI
Native apps where the model runs on the phone, not in the cloud. Privacy-first architecture with encrypted local storage.
Web Apps and Real-Time Platforms
Live data platforms on edge infrastructure. Zero server cost when traffic is zero, full capacity when it spikes.
AI Integration and Automation
Connecting systems, migrating data, and automating operations under supervision. CRM hygiene, API integrations, and agents that do repetitive work.
AI Adoption Consulting
Where AI fits in your operation and how it ships. Audit, roadmap, pilot, production. No theory without proof.
WordPress Development
Custom block themes, mu-plugin architecture, SSH-only deploys, and Cloudflare-sole caching. No page builders, no bloat plugins.
SERVICE CASE STUDIES
This site. Taken off a page builder and rebuilt as a hand-written WordPress block theme, ported from the design components rather than drawn a second time.
Independent review of one problem across architecture, engineering, marketing, sales, and research. What arrives is a written blueprint you own and can execute with or without Zedlav.
Not an agency with AI tools.
- Buys a subscription and calls it a capability
- Demos in a deck, delivers in a spreadsheet
- Output nobody checked against a source
- Runs the same playbook on every client
- Builds and operates its own infrastructure
- Builds apps end to end and keeps them up
- Citation and anti-fabrication enforced in code
- Every risky change gated behind human approval
Eight steps. One of them stops.
The work moves fast because it is narrow at the front: one problem, one blueprint, one decision. Then execution runs wide. Step 04 is a real gate, and no-go is a real outcome.
Problem statement
You describe what is slow, manual, or breaking. It becomes one written sentence you sign off on before anything else happens.
Multi-agent analysis
Parallel passes over your stack, data, and constraints. Findings arrive with sources attached, or they do not arrive.
Blueprint
Architecture, deploy target, running cost, and what happens when it fails. Written before a line of code is committed.
Go / no-go
A person reads the blueprint and decides. Nothing downstream can start without it, and no-go costs you nothing.
Priority tasks
The blueprint splits into ordered work, sequenced so the risky parts land first while there is still room to change course.
Build
Execution runs wide and fast. Every file that reaches you is verified before release, so speed never arrives at the cost of review.
Host
Your own hardware, your cloud account, or Zedlav’s edge. You own the deploy target, which means you can take the thing with you.
Go live
Baseline captured, drift watched, rollback ready. Launch is where monitoring starts, not where the engagement ends.
Send the problem.
Not the spec.
One sentence on what is slow, manual, or breaking is enough to start. You get a blueprint conversation, not a sales call.
sales@zedlav.ai →