Softment

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.

TimelineTypical: 2–5 weeks (scope-dependent)
Starting at£1.4k
Security-first AI integrations • Evals + logging + guardrails included

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

1
2–4 days

Baseline + dataset

We gather sample queries and define retrieval metrics for your success criteria.

2
4–10 days

Hybrid retrieval build

We implement hybrid retrieval and filters on your chosen search + vector stack.

3
1–2 weeks

Reranking + tuning

We integrate reranking and tune weights/thresholds against your dataset.

4
3–7 days

Latency hardening

We optimize and add caching so quality improvements don’t slow responses.

Tech Stack

Technologies we use

Core

BM25 + keyword searchEmbeddings + vector searchReranking modelsVector DBs + metadata filters

Tools

Eval datasetsCaching (Redis)

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.

Regional

Delivery considerations for your region

Compliance & Data (UK/EU)

For UK teams, we default to GDPR-first thinking: data minimisation, purpose-limited storage, and clear access boundaries.

We can work under a DPA (template available on request) and implement practical retention/deletion flows when needed.

  • GDPR-first patterns (minimise, restrict, document)
  • DPA template available on request
  • Retention/deletion and export flows where required
  • Least-privilege access and secure session handling
  • PII-safe logging + secure-by-default configuration
  • NDA available for early-stage discussions

Timezone & Collaboration (UK/EU)

We align to UK time and EU overlap (GMT/BST with CET-friendly windows) for fast feedback cycles.

We keep the process lightweight: async updates, clear priorities, and written decisions to avoid ambiguity.

  • UK/EU overlap with GMT/BST windows
  • Async-first delivery with documented scope
  • Weekly milestones and structured demos
  • Clear escalation path for blockers
  • Tight change control with clear sign-offs

Engagement & Procurement (UK)

We support typical UK procurement flows with clear scopes, change control, and invoice cadence.

If you prefer a discovery-first engagement, we can run a short paid discovery to lock requirements before build.

  • GBP-based engagements and invoicing options
  • Discovery-first option to reduce delivery risk
  • Milestone-based billing when appropriate
  • Transparent change control and sign-offs
  • Vendor onboarding pack on request

Security & Quality (UK/EU)

We build for reliability and maintainability: clean PRs, tight review loops, and test coverage that matches risk.

Performance budgets and release checklists keep launches predictable—especially when multiple stakeholders review changes.

  • CI-friendly testing: unit + integration + smoke tests
  • Performance budgets + bundle checks (Core Web Vitals-minded)
  • Structured release notes and rollback-safe deployments
  • Security checklist for auth, roles, and data flows
  • Observability hooks (logs + error tracking) ready for production
Ready to start?

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.