AI Development
Hybrid Search & Reranking Services
We improve retrieval quality using hybrid search and reranking: higher recall, better relevance, fewer misses, and measurable tuning for RAG assistants and semantic search products.
Overview
What this service is
Hybrid retrieval combines keyword and vector search so you get both exact-match precision and semantic recall for messy real-world queries.
Reranking improves relevance by scoring candidate results more carefully, reducing wrong context that causes poor answers in RAG systems.
We tune retrieval using a query set and metrics, then harden latency and caching so quality gains don’t create performance regressions.
Benefits
What you get
Higher recall for long-tail queries
Find relevant context even when users don’t use the exact same wording as your documents.
Fewer hallucinations in RAG
Better context selection reduces wrong answers caused by irrelevant or missing sources.
Better ranking for mixed content
Hybrid retrieval handles structured docs, FAQs, and long-form PDFs with stronger relevance.
Measurable quality improvements
Tuning is validated against a dataset so changes are repeatable and trackable.
Latency-aware design
Caching and query optimization keep response time fast as traffic grows.
Features
What we deliver
Hybrid retrieval implementation
BM25 + vector search composition, weighting, and query expansion for better recall.
Reranking integration
Cross-encoder or LLM-based reranking with thresholds and explainable diagnostics.
Metadata filters
Filters for doc type, product version, tenant/team boundaries, and access control patterns.
Retrieval evaluation
Query sets and metrics for relevance and coverage, with regression checks over time.
Latency optimisation
Candidate limits, caching, and batching strategies to keep retrieval fast and cost-aware.
Debug tooling
Expose retrieved chunks and scores so teams can inspect why an answer happened.
Process
How we work
Baseline + dataset
We gather sample queries and define retrieval metrics for your success criteria.
Hybrid retrieval build
We implement hybrid retrieval and filters on your chosen search + vector stack.
Reranking + tuning
We integrate reranking and tune weights/thresholds against your dataset.
Latency hardening
We optimize and add caching so quality improvements don’t slow responses.
Tech Stack
Technologies we use
Core
Tools
Use Cases
Who this is for
Support knowledge search
Improve recall and relevance across product docs, FAQs, and troubleshooting guides.
Internal policy assistants
Rank the right policy excerpt first, with filters for department and document version.
Product documentation copilots
Retrieve the most relevant sections from long docs and reduce wrong-context answers.
Search across PDFs
Handle long, noisy PDFs with hybrid retrieval and reranking tuned for real queries.
Multi-tenant RAG systems
Prevent cross-tenant leakage using strict filters combined with relevance scoring.
FAQ
Frequently asked questions
Not always. For many domains, hybrid retrieval improves recall significantly, especially when users ask in varied language or include product codes and exact terms.
It depends on constraints. We can use smaller rerankers for speed, or higher-quality reranking where accuracy is more important than latency.
It often does, because better retrieval reduces wrong context. We also recommend evals and guardrails for end-to-end reliability.
Yes. We expose retrieved chunks and scores so teams can debug and tune retrieval behaviour.
Yes. We can improve retrieval on top of your current ingestion and vector DB setup with minimal disruption.
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Regional
Delivery considerations for your region
Compliance & Data (AU)
For Australian teams, we keep privacy and data-handling explicit: access boundaries, safe logging, and clear retention policies.
We can support residency-sensitive designs (where feasible) and document data flows for stakeholder review.
- Privacy Act-aware delivery posture (generic, no legal claims)
- Documented data flows and access boundaries
- Retention/deletion options where required
- PII-safe logging and least-privilege defaults
- NDA and DPA templates available on request
Timezone & Collaboration (APAC)
We support APAC collaboration with AEST/AEDT-friendly meeting windows and async progress updates.
We keep momentum with weekly milestones, crisp priorities, and predictable release planning.
- APAC overlap with AEST/AEDT windows
- Async-first updates and written decisions
- Weekly milestone demos and scope control
- Release planning with staged rollouts
- Clear escalation path for blockers
Engagement & Procurement (AU)
We can structure engagements with clear scope, milestones, and invoicing that fits common procurement expectations.
If you need a lightweight vendor onboarding pack, we can provide delivery process notes and security posture summaries.
- AUD-based engagements and invoicing options
- Milestone-based billing for fixed-scope work
- Time-and-materials for evolving scope
- Procurement-friendly documentation on request
- Optional paid discovery to de-risk delivery
Security & Quality (APAC)
With APAC teams, async clarity matters: written decisions, stable releases, and test coverage that prevents regressions.
We use performance budgets and release checklists so handoffs stay smooth across timezones.
- CI-friendly testing: unit + integration + smoke tests
- Performance budgets + bundle checks
- Release checklist + rollback plan for production launches
- Security checklist for auth and sensitive data flows
- Observability hooks (logs + error tracking) ready for production
Want better retrieval without guesswork?
Share your queries and content—we’ll tune hybrid search and reranking with an eval set and measurable targets.
Eval-driven improvements.