AI governance
All industries
AI CONSULTING FOR TECHNOLOGY + IT SERVICES
AI for engineering velocity and customer impact — without breaking SOC 2.
For SaaS vendors, MSPs, system integrators and IT consultancies (30–300 staff): the AI value lands in engineering velocity, customer-support deflection and internal knowledge — not in shipping a chatbot you cannot defend in a SOC 2 audit. Microsoft AI + GitHub Copilot deployed inside the SOC 2 / ISO 27001 / GDPR controls your customers and auditors already expect.
Where it shows up first
Three signals AI is the right call for your technology firm right now.
Engineering velocity has plateaued mid-roadmap.
GitHub Copilot is installed but acceptance rates and meaningful productivity uplift have stalled. We run a measured rollout — baseline metrics, target patterns, code-review guardrails, language-specific prompt packs — so the spend turns into shipped PRs, not seat licences.
Customer support drowns in tier-1 tickets.
CS engineers spend their week on the same handful of questions while the strategic tickets wait. A Copilot Studio agent grounded in your product docs + KB + release notes deflects the routine and hands tier-2 a structured handoff with the diagnostics already attached.
Internal knowledge lives in three Slack channels and one ex-employee.
New-hire ramp and senior-engineer interrupt rate are both too high. A citation-grounded agent over your runbooks, ADRs, design docs and incident post-mortems returns the answer with the source attached — and quietly surfaces where the docs are missing.
What we ship
Four patterns that move the needle in technology & it services.
#1
GitHub Copilot acceptance + velocity rollout
Baseline acceptance + cycle-time metrics, language-specific prompt packs, code-review guardrails for AI-authored diffs, custom instructions per repo. Turns Copilot from a per-seat line item into a measurable PR-throughput lift.
GitHub Copilot Business / Enterprise
#2
Customer-support AI assist agent
Copilot Studio agent over product docs, knowledge base, release notes and the past 12 months of resolved tickets. Drafts first responses, deflects the routine, hands tier-2 a structured handoff with the diagnostics already attached.
Copilot Studio + Azure OpenAI
#3
Internal knowledge agent for engineering
Grounded in your runbooks, ADRs, design docs, incident post-mortems and the on-call rotation. Returns cited answers; flags where the docs are stale or missing so the team can fix the source, not just the symptom.
Copilot Studio + Microsoft 365 Copilot
#4
Security-incident triage copilot
Agent that summarises the alert, correlates with recent deploys + on-call notes, drafts the first-cut incident timeline and the customer-facing status update. The on-call SRE remains the decision-maker; the agent removes the typing.
Azure OpenAI + Microsoft Sentinel
The governance posture
Tech and IT-services firms are the most audit-aware buyers we sell to — your customers ask you SOC 2 / ISO 27001 / GDPR questions before they ask you product questions. Our deployments default to: AI workloads inside your existing Microsoft 365 / Azure tenant boundary so they inherit your existing SOC 2 controls and sub-processor map; Microsoft’s DPA + commercial terms cover the data-processing posture your customers expect; GitHub Copilot deployed under the Business / Enterprise plan so completions stay out of model training; AI-authored code is reviewable by a human under your existing code-review policy; nothing we deploy bypasses your secret-scanning, dependency-scanning or change-management controls. The deployment memo is written so your customer-security team can drop it straight into the next SOC 2 audit and the next customer security questionnaire.
The stack, vertical-specific
The four Microsoft tiles that light up first in technology & it services.
The same six-tile Microsoft AI stack runs everywhere, but the order in which the tiles pay back differs by vertical. Here’s the order we ship for technology & it services firms.
GitHub Copilot Business / Enterprise
In the engineering seat
Code completion, chat, PR summarisation and code review inside your existing GitHub org. Business / Enterprise plans keep completions out of model training and integrate with your SSO + audit log so the SOC 2 story is one line longer, not one binder larger.
Microsoft 365 Copilot
In the GTM + ops seat
Drafts sales emails, customer QBR decks, internal status updates and roadmap memos inside the tenant your customers already trust. Honours your Purview labels so customer-confidential content does not leak into a marketing draft.
Copilot Studio + Azure OpenAI
Customer + internal agents
Customer-support deflection agents, internal knowledge agents and product-trial guidance bots. Grounded in your docs, KB and tickets; citation-backed so support engineers and customers can verify the source in one click.
Microsoft Purview + Sentinel
Customer-data containment + SOC story
Sensitivity labels on customer data, PII, source code and incident data. DLP keeps labelled content out of AI drafts; Sentinel correlates AI agent activity with the rest of the SOC telemetry so the customer-security questionnaire answers itself.
Writing for technology leaders
Three pieces of our published thinking on technology.
Where this leads next
Two more paths if you want to go deeper on technology.
Common questions
What firms in technology & it services usually ask first.
Does GitHub Copilot keep our code out of model training?
On the Business and Enterprise plans, yes — completions and prompts are excluded from training. We default to one of those plans for every engagement and configure the org-level policies (suggestion matching, public-code filter, audit-log retention) before we turn anyone on.
How does this fit our existing SOC 2 / ISO 27001 posture?
AI workloads run inside your existing Microsoft 365 / Azure / GitHub tenant boundary, so they inherit your existing controls and sub-processor map. We supply the deployment memo + sub-processor delta + customer-questionnaire answers that bolt onto your next SOC 2 audit without rewriting it.
Will AI agents merge code or push to production?
No. Every AI-authored diff goes through your existing code-review policy with a human reviewer named on the PR. Agents draft, suggest, summarise and triage; humans merge and deploy. The audit trail is identical to a human-authored PR.
Can the customer-support agent see customer PII?
Only the data your existing support tooling already exposes to the support engineer. We do not introduce new data flows. Purview labels keep customer-confidential content out of any draft the agent generates, and every cited answer points back to the source ticket or doc so the engineer can verify scope.
Ready to map this to your technology firm specifically?
Eight minutes, no obligation. The free AI Readiness Assessment is calibrated for technology & it services workflows and surfaces the highest-value pattern from this page for your specific situation.