
1
1
Philippines
4+ years of experience
hey! i’m a 4th year BS information Technology student all for building and shipping products that feel intuitive and meaningful. i work at the crossroads of design and development, as it lets me think about people first and then figure out how to turn ideas into something real and human. my belief is in innovation that can bridge even the farthest places. growing up, i've seen how technology has proven itself to have the power to connect people, solve problems that feel out of reach, and create opportunities that make life easier. along the way, i’ve learned how to collaborate, communicate clearly, and work even in fast-moving environments; always listening, trying to understand, and always aiming to build something that has real value. outside of tech, i enjoy shooting and editing videos, cooking, horror movies, story games and listening to k-pop 🐰

Every law firm sits on an unmined fortune: the experiential wisdom of senior partners. Yet, when a veteran attorney retires or departs, decades of strategic instinct permanently evaporate. This institutional knowledge loss costs mid-to-large firms $15M to $40M annually. The barrier to documentation is economic. Lawyers bill in six-minute increments; spending time writing down lessons represents an immediate loss of billable revenue. While generative AI should solve this, strict obligations toward attorney-client privilege block public LLM tools. Meanwhile, vertical legal tools like Harvey provide generic legal advice but lack a firm's specific internal wisdom. Trellis solves this with a secure, two-tier system architecture. The first layer is the Personal Second Brain. This is a private, on-device edge environment running Gemini Nano where attorneys quickly capture unstructured thoughts via voice memos, notes, or image OCR. Because data stays local, capture is entirely unredacted and factual. The second layer is the Team-Managed Knowledge Graph. This shared ledger is built through an automated, dual-pass sanitization pipeline. First, Microsoft Presidio strips explicit PII like names, dates, and entities. Second, Gemini Pro abstracts the specific case details into generalized strategic principles. The lawyer reviews a side-by-side diff before approving publication to the firm's shared memory. Using a hybrid vector-graph RAG model, team members can query this collective intelligence using natural language. To eliminate legal risk, Trellis enforces a hard deterministic guardrail: if the retrieved context score falls below a strict threshold, the system executes a strict refusal rather than risk a hallucination. Finally, Trellis exposes a Model Context Protocol (MCP) endpoint. This allows third-party tools like Harvey, CoCounsel, or Copilot to securely plug directly into the substrate, grounding generic legal AI capabilities in the firm's actual historical wisdom.
19 May 2026