Find - Data, search & analytics
Search experiences, indexing, and query design for relevance and speed at scale.
When users need to find the right thing in a sea of data, naive queries break down. We design and tune search-heavy features using OpenSearch or Elasticsearch: index design, analyzers, and query patterns that match how people actually search—whether that is a customer-facing catalog or an internal recommendation-style workflow.
What we focus on
Index mappings and refresh strategies that balance freshness and cost.
Relevance tuning: boosts, filters, and evaluation against real queries—not vanity metrics.
Operational concerns: clusters, backups, and capacity as usage grows.
Beyond the index
Pairing search with your primary database so writes and reads stay consistent with your product rules.
Exposing search through APIs your application team can consume without leaking infrastructure details.
Common questions
- How do you usually engage with clients?
- Most work is structured as a project: clear scope, milestones, and deliverables. When ongoing evolution, support, or a fractional engineering partner makes sense, we can discuss a retainer—after we have a shared sense of fit and priorities.
- What does an early milestone look like?
- We align on outcomes and constraints first, then break work into increments you can review—often starting with architecture notes, a thin vertical slice, or a hardening pass on the riskiest area, depending on the engagement.
- Can you work with our existing stack and team?
- Yes. We integrate with your repositories, processes, and people. The goal is sustainable handoff: patterns your team can own, documentation where it helps, and automation that reduces repeat mistakes.
- How do you talk about AI and automation?
- We use AI and APIs where they remove real toil or improve quality—workflow automation, integrations, assistive tooling—with clear guardrails, logging, and human review when the domain requires it. No hype, no mystery boxes.