Softment

AI Development

AI Evaluation & Testing

We build evaluation and testing systems for LLM products: golden datasets, automated scoring, human review loops, and regression gates. This turns “it feels worse” into measurable signals your team can ship against. Delivery aligned to United Kingdom teams (GBP).

TimelineTypical: 2–5 weeks (scope-dependent)
Starting at$1.2k
Security-first AI integrations • Evals + logging + guardrails included

Overview

What this service is

AI evaluation is how you measure quality and prevent regressions across prompts, models, retrieval settings, and tool behaviors.

We define realistic test sets and scoring criteria, then automate evaluation so changes can be reviewed and shipped safely.

Delivery includes dashboards and workflows so teams can iterate quickly without losing trust in production behavior.

Standard

AI delivery standard

Quality and safety practices we ship with AI builds so the system stays measurable, maintainable, and production-ready.

Logging + tracing

Conversation and tool traces with request IDs, error visibility, and debug-friendly runbooks.

Guardrails + safety

Tool allowlists, PII-safe patterns, refusal behavior, and escalation routes for edge cases.

Evals + regression tests

Golden queries, scorecards, and regression checks so quality improves over time instead of drifting.

Cost + latency controls

Caching, prompt discipline, retrieval tuning, and routing so your app stays fast and predictable at scale.

Documentation + handoff

Architecture notes, environment setup, and next-step roadmap so your team can iterate safely after launch.

Security-first integration

Secrets isolation, role-based access, audit-friendly actions, and minimal data retention by design.

Benefits

What you get

Catch regressions before they hit users

Measure quality improvements with real metrics

Reduce subjective debates with shared eval criteria

Improve safety with red-team test coverage

Ship model/prompt changes confidently

Prioritize fixes using labeled failure modes

Features

What we deliver

Golden datasets

Representative test queries and expected behaviors based on real user intents and business rules.

Automated scoring

Scoring for relevance, correctness, format, citation quality, and policy compliance with repeatable runs.

Human review loops

Sampling-based review workflows to label failures and improve datasets over time.

Regression gates

CI-style checks that fail builds when quality drops below thresholds for key intents.

Safety and red-team tests

Prompt injection, policy-violating requests, and adversarial scenarios to validate guardrails.

Dashboards + reporting

Visibility into quality trends, failure clusters, and “what changed” between releases.

Process

How we work

1
2–4 days

Define criteria

Success metrics, intents, and failure taxonomy.

2
4–10 days

Build datasets

Golden queries + expected behaviors.

3
1–2 weeks

Automate scoring

Repeatable evaluation runs and reporting.

4
3–6 days

Add gates

CI checks and thresholds for release control.

5
Ongoing

Review loop

Human labeling workflow and iteration plan.

Tech Stack

Technologies we use

Core

Evaluation datasetsAutomated scoringRed-team testsTracing

Tools

CI gatesRAG metricsNode.js / PythonPostgreSQL

Services

Sentry / monitoringDashboards

Use Cases

Who this is for

RAG accuracy validation

Evaluate retrieval precision and citation quality on real queries and content changes.

Chatbot regression protection

Prevent prompt or model changes from degrading user-facing answers and escalation behavior.

Tool-action correctness testing

Validate that agents call the right tools with the right parameters under edge cases.

Safety validation

Test prompt-injection defenses and refusal behavior against adversarial user inputs.

Enterprise rollout reporting

Produce quality reports and release notes that stakeholders can trust.

AI Case Examples

Micro case studies (anonymous)

A few safe examples of outcomes we build for real operations—no client names, just results.

Secure Mobile Solution in Australian Defence Ecosystem

Problem: Secure data workflows were required in a regulated environment with strict access controls.

Solution: Hardened architecture with strict auth, encrypted storage, and audit-friendly engineering patterns.

Outcome: Deployed securely within a regulated ecosystem with clear handoff and operational guidance.

AI Knowledge Base Across 2,000+ Pages

Problem: Teams needed fast answers across long PDFs, but search was slow and results were inconsistent.

Solution: RAG with hybrid retrieval and reranking, plus grounded answers and safer fallback behavior.

Outcome: Reliable answers with <10s response times and measurable improvements on real queries.

Ops Automation with AI + n8n

Problem: Manual approvals and CRM syncing created delays and data inconsistencies across tools.

Solution: Event-driven automation with validation gates and AI-assisted classification where it improved routing.

Outcome: Reduced manual workload significantly with more reliable workflows and operator visibility.

FAQ

Frequently asked questions

Done right, they speed it up. Teams ship changes faster when they can see impact and avoid regressions early.

Usually both. We score relevance, correctness, formatting, citation quality, and safety depending on the product.

Yes. We include adversarial test sets and safety checks aligned to your policy and guardrails.

For most real products, yes. Sampling-based human review helps validate edge cases and keeps datasets honest.

Yes. We design evaluation runs and budgets so you can run meaningful checks during CI without excessive cost.

Datasets, scoring scripts, dashboards, and runbooks for expanding coverage over time.

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 help with AI evaluation and testing?

Get a clear plan for United Kingdom teams—scope, timeline, and next steps. GBP-based engagements.

Reply within 2 hours. No-pressure consultation.