Services
We work with compliance-sensitive enterprises and the vendors who sell to them. Three lanes; one engagement model; no six-month discovery phase.
Cloud cost & FinOps strategy
When to call us
You are about to make a multi-year cloud commitment and the internal numbers do not agree. Your incumbent hosting provider will not share invoices. A board paper is due in three weeks. You are a SaaS vendor pricing a multi-installation deal and need to know what to charge before you quote it. Your CSP renewal is up and the partner-margin question has nobody to defend it.
What we deliver
A board-grade cost assessment anchored on published cloud-economics frameworks — Hugo & Rey on FinOps structure and chargeback, Kline et al. on managed-instance tier selection and migration effort, Campbell & Majors on SLA and DR cost modelling, and three more depending on the engagement.
Typical deliverables include a four-category cost taxonomy (fixed overhead, competence, variable, per-server), multi-scenario reserved-instance and CSP-margin modelling, a triangulated baseline against incumbent spend, sensitivity analysis on staffing posture, and a working cost-model spreadsheet you keep.
What we do not deliver
We do not write Terraform. We do not migrate workloads. We do not sell you a product or a partner relationship. We deliver the document the decision-maker reads.
Recent example
A multi-installation industrial software vendor needed to know what to charge an enterprise customer for a cloud-managed deployment. The incumbent hosting baseline was unavailable. We built a triangulated baseline from public cloud list pricing and typical partner-margin bands, modelled three pricing scenarios across two staffing postures, and delivered a per-installation pricing playbook plus an enterprise-side calculator the customer could populate with their own numbers. Forty-hour fixed-scope advisory. Read full case study →
Cyber resilience & NFR advisory
When to call us
Your enterprise customer just sent you their NFR catalog and you have ninety days to respond. NIS2 transposition has started touching your operating perimeter and the in-house team is missing one specific area. You are drafting the NFR catalog itself for an upcoming procurement and want it audit-defensible. Your pre-contract due diligence keeps stalling on the same five questions.
What we deliver
Structured NFR compliance responses against enterprise procurement matrices. We work across the standard domains — cyber security, data architecture, technical architecture, business continuity. Each response carries a compliance status (compliant / partial / non-compliant / desirable), justification, evidence trail, action required, and cost-impact estimate.
Around the register itself we add structural artifacts the original catalog often does not ask for — a deep-dive for the items that do not fit a row, a source-verification log linking each justification to the underlying meeting or document, and a consolidated cost-impact summary that surfaces renegotiation triggers up front rather than mid-procurement.
We work with Azure-native security stacks (Entra ID, Key Vault, Defender, Purview, Sentinel) but the methodology is platform-agnostic.
What we do not deliver
We do not conduct penetration tests or security audits. We do not sit on your CSIRT. We do not write your ISO 27001 policies from scratch. We deliver structured advisory — the kind of document that turns a vague we'll be compliant into a defensible position.
Recent example
A tier-1 European energy operator's procurement NFR matrix carried roughly fifty line items across cyber security and data architecture domains. The vendor needed a structured response that would survive procurement review, with evidence trails for partial-compliance items and a separate cost-impact tab for non-compliant ones. We produced the response register, a deep-dive sheet for the difficult items, and a source-verification log linking each justification to the underlying meeting or email. Pre-contract due diligence engagement. Read full case study →
AI integration for established systems
When to call us
You have working systems and you want to connect modern frontier models to them — not replace them. Your data-residency requirements rule out hosted LLM APIs. Your knowledge base is too large to paste into a prompt and too sensitive to upload to a third party. Your engineering team has shipped a chatbot and now leadership wants to know is this actually working?
What we deliver
Five common engagement shapes:
- MCP control layers wrapping existing internal applications, exposing them as tools to LLM agents.
- RAG over enterprise knowledge bases — including chunking strategy, retrieval tuning, evaluation harness, and an honest answer to is RAG the right call here at all?
- On-premises LLM infrastructure — model selection (Llama family, Mistral, others), serving stack (Ollama / vLLM), GPU sizing, observability.
- LLM-assisted legacy modernization — using frontier models to accelerate code understanding, dependency mapping, and migration planning on systems your team has been told to just rewrite.
- AI training for engineers and managers — what these systems are, what they are not, and how to evaluate them empirically.
What we do not deliver
We do not train foundation models. We do not sell you AI strategy without a working artifact at the end. We will not ship an AI feature where the right answer is a SQL query.
Recent example
We are holding the most recent AI integration cases until the relevant clients clear public reference. The general shape is: PoC in two to four weeks, evidence-based go/no-go, and either a production roadmap or a clean exit from a project that should never have been an AI project to begin with.
How we work
We run three engagement shapes:
Discovery Sprint — one to two weeks. Scoped question, structured assessment, decision-ready output. Typical for should we go to cloud, is this NFR response defensible, or is RAG the right shape for this problem. Fixed fee.
Rapid PoC — two to four weeks. Working demonstration plus an evidence-based go/no-go recommendation. Typical for AI integrations and modernization questions where the team needs to see something running before it commits. Fixed fee.
Fractional advisory — ongoing retainer. Architectural sounding-board for the in-house team, second-opinion reviews on RFPs, technical due diligence on vendor proposals. Typical when the in-house team is strong but missing one specific area of depth. Monthly minimum.
We take one to two new engagements per quarter. The first thirty minutes is always free, with no pitch and no slide deck. If we do not think we can help, we will say so.