AI LabsbyThe Ops ToolboxOps Toolbox

What we do

Types of work

Hands-on advisory for leaders and platform teams — backed by 25 worked examples with live demos, diagrams, and delivery playbooks.

Worked examples and decision guides you can run in reviews and pilots — an evidence base from The Ops Toolbox.

Transformation assessment

1 to 2 weeks · fixed scope

Architecture & governance review

2 to 3 weeks · fixed scope

Pilot squad

4 to 8 weeks · time & materials or capped

All engagement shapes
Jira
AI portfolio & prioritization
Cut through the backlog of “we should do AI” ideas. Align use cases to measurable outcomes, risk appetite, and the systems you already run.
  • Ranked initiative shortlist with success metrics
  • Build vs buy vs partner framing per workload
  • Executive-ready narrative, not a 100-slide deck

Related examples: Transformation Discovery with Claude Structured Output, Meeting Notes to Action Items with Claude

Architecture & pattern selection
Pick the right design for your workflow — live assistant, searchable documents, model routing, or a governed multi-step process — on the cloud you already use.
  • Reference architecture with explicit tradeoffs
  • Integration points to CRM, ticketing, and identity
  • Diagrams and notes your engineers can challenge in review

Related examples: Operational Copilot with Streaming Tools, Enterprise RAG on Azure AI Foundry, Policy Q&A with seed RAG, Multi-model routing via unified gateway, Intent Routing on Amazon Bedrock

Governance, safety & human oversight
Design escalation paths, approval rules, and safety checks before AI can change customer-facing systems.
  • Escalation matrix and supervisor handoff model
  • Input/output safety thresholds aligned with legal
  • Audit-friendly step timelines for orchestrated flows

Related examples: Operational Copilot with Streaming Tools, Human-in-the-Loop Approval Gates, Prompt A/B Evaluation with Structured Rubrics, Batch ticket triage, Intent Routing on Amazon Bedrock, Responsible AI Gate with Azure Content Safety, Agent Orchestration on Azure AI Foundry

Pilot delivery & hardening
Stand up a six-week pilot with real routes, seed or production-adjacent data, and clear criteria to expand, or stop.
  • Working pilot in your tenant or ours, with runbooks
  • Discovery → pilot → scale playbook with honest weeks
  • Handle-time, override, and grounding metrics defined up front

Related examples: Durable multi-step orchestration, AWS-Native Q&A with Amazon Bedrock, Orchestrated Agents on AWS Bedrock

Platform & engineering enablement
Help platform teams own model routing, monitoring, and shared patterns — so product squads are not each building their own AI stack.
  • Shared tool schemas and policy-as-code patterns
  • Gateway routing and cost guardrails
  • Code review standards for agentic features

Related examples: Multi-model routing via unified gateway, Production Observability for AI Routes, Durable multi-step orchestration, Prompt A/B Evaluation with Structured Rubrics, Intent Routing on Amazon Bedrock

Google Cloud
Technical reviews & diligence
Second opinion on vendor proposals, internal builds, or acquired products, before you sign the enterprise agreement or merge the team.
  • Risk register tied to architecture choices
  • Gaps in IAM, data residency, and eval discipline
  • Clear go / pivot / stop recommendation

Related examples: Azure OpenAI Chat Baseline, Enterprise RAG on Azure AI Foundry, Prompt A/B Evaluation with Structured Rubrics

Outcomes we repeat

Typical results when the pattern fits your context.

Architecture review or 6-week pilot

Regulated policy Q&A with source citations

Financial services, insurance, and large HR policy estates

  • Citation rate above 90% on an agreed golden question set
  • Documented unknown-answer path when retrieval is weak
  • Quantified lift vs general chat baseline for audit

Pilot squad with steering forum every week

Operations assistant with human approval

Support, ITSM, and CRM-adjacent workflows

  • Read-only access in pilot; updates only after supervisor approval
  • Handle time improvement on covered intents with quality sampling
  • Incident and override metrics in the same dashboard as cost

1 to 2 week assessment

Portfolio prioritisation and council operating model

Medium and large programmes with many AI ideas

  • Single intake scorecard and capped active pilots
  • Named champions with protected time and enablement kit
  • Scale / pivot / stop decisions documented per pilot

Architecture review then pilot on one squad

Platform standards and model routing

CTO office standardising models, logging, and cost

  • Default model per task type with documented fallback
  • Structured logs and eval CI on prompt or index change
  • Cost per successful task visible to finance monthly

2 to 3 week review alongside build team

Security and privacy gate before production

InfoSec review before an AI assistant or document Q&A goes live

  • Evidence pack accepted by risk (diagrams, logs, quality checks)
  • Pen test on tool endpoints, not chat UI only
  • Runbook drill for disable-tools and human fallback

Workshop plus architecture review

Copilot coexistence and custom systems of record

Microsoft-centric enterprises with M365 Copilot licensed

  • Channel matrix: Copilot vs custom app vs human queue
  • Custom work scoped to CRM/ITSM updates and cite-only document sets
  • Aligned retention and safety rules across channels

What we do not sell here

Managed hosting, 24×7 model operations, or open-ended prompt tuning. Engagements are scoped to decisions, pilots, and enablement you can own — in your cloud, within your data boundaries, with your escalation paths.

Next step

Plan your next pilot

Worked examples and decision guides you can run in reviews and pilots — an evidence base from The Ops Toolbox.

Email NedContact form on The Ops Toolbox

Prefer the web form? The Ops Toolbox.

  • One workflow, clear metrics
  • Your cloud, your keys
  • Written handoff, not dependency