Trusted By
Already Live in Enterprise Environments
Solution Overview
Governance That Actually Reaches Production
Adastra pairs governance consulting with AGate’s runtime controls, reusable accelerators, and hands-on delivery. The framework doesn’t stop at a slide deck — it runs in your environment.
Advisory & Framework
Governance operating model, risk classification, and policy design.
AGate Control Plane
Runtime cost, access, and audit control in your tenant.
Governance Accelerators
Registries, workflows, and evaluation tooling, ready to reuse.
Challenges
AI Is Already Running Ahead of Your Governance
Shadow AI, spend with no owner, oversight split six ways — it’s already happening inside your walls. Most enterprises have no single, enforced way to govern any of it.
Shadow AI Everywhere
Teams already use tools nobody approved, and every one is a data, compliance, or accountability gap waiting to surface.
Pilot Purgatory
Good use cases stall with no intake, no lifecycle controls, and no way to evaluate them — so nobody can prove the return.
Regulatory Pressure Mounting
OSFI E-23, the EU AI Act, and emerging US guidance turn what was optional into an obligation — on a timeline you don’t control.
Governance Split Six Ways
Risk, legal, security, and data each own a piece, and none of those controls talk to each other.
Spend With No Owner
Nobody set a budget for token, cloud, or agent usage, so it grows until someone finally asks who owns the bill.
Trust That’s Slow to Earn Back
Hallucinations, bias, and weak monitoring erode trust fast with regulators, boards, and customers — and it’s slow to rebuild.
Solution
How We Make Governance Operational
Governance design and runtime enforcement, in one program. Policy stops mattering the moment it stops touching production — so we built both into the same offer.
AI Governance Consulting
Assessment · Operating Model · Roadmap
- Current-state assessment of AI usage, risk, and controls
- Target operating model with clear decision rights
- Risk classification and policy design
- AI literacy and a costed, actionable roadmap
AGate Control Plane
Cost · Access · Audit
- One governed layer for all AI traffic
- Single sign-on and role-based access control
- Spend budgets and cost visibility
- Agent observability and full audit trails
Governance Accelerators
Registry · Intake · Evaluation
- AI use-case and agent registry
- Intake and approval workflows
- Reusable policy libraries
- LLM evaluation environment
Agentic AI Controls
Guardrails · Kill Switches · Escalation
- Runtime guardrails for autonomy and tools
- Prompt and output controls
- Kill switches and incident escalation
- Governance embedded where agents run
Outcomes
Faster AI, With the Controls Already Built In
Governed AI adoption doesn’t slow you down. It’s what gets use cases into production faster, with less rework and cost you can actually track as you scale.
How We Work
A Staged Path That De-Risks the Investment
You approve the model and the controls first. Nothing gets built in your environment until you sign off, and every phase after that stands on proof from the one before.
Assess
We map your AI landscape end to end — tools, models, agents, policies, and data risks. You leave with prioritized gaps and a costed roadmap you can act on right away.
Design
Decision rights, risk classification, policies, and lifecycle processes: we define the target operating model, then design the tooling blueprint you approve before anything gets built.
Deploy AGate & Accelerators
AGate goes into your tenant, configured with SSO, RBAC, spend visibility, and audit trails. Then we stand up the registry, intake workflow, and evaluation environment your teams run day to day.
Implement Pilot Controls
Intake, risk assessment, approval, monitoring, and incident response applied to one to three priority use cases or agents — so the model proves itself in production, not on paper.
Scale Governance-as-Code
For higher-autonomy agentic workflows, we embed controls for access, prompts, tools, and cost directly into your runtime and platform layer, so governance travels with the workflow.
Enable Adoption
Playbooks, training, communications, and support through your first governed use cases. After that, the capability is yours to run and extend.
Why Adastra
Why Enterprises Choose Adastra for AI Governance
We build the framework and enforce it ourselves. Nothing you adopt here stays theoretical, because we’re the ones who have to make it work.
Governance and Enforcement, Together
We design the operating model, then implement the runtime controls ourselves through AGate. Most firms leave the gap between policy and production open. We close it.
Built for Speed, Not Sign-Offs
This isn’t another layer of committees. The offer is built for speed to value, and for as little friction as your AI teams can tolerate.
Multi-Cloud by Design
AGate runs inside your own cloud tenant, giving you one control point across Microsoft, AWS, and third-party model providers at the same time.
Data and AI Governance, Together
Trustworthy AI depends on governed data as much as governed models, so we bring data governance and AI governance methodology together instead of separately.
A Track Record You Can Check
Banking, pharma, telecom — the references are real, and the cited outcomes include production use cases, audit readiness, and cloud cost savings you can verify.
An Implementation Partner, Not Just an Advisor
We design it, deploy it, and operationalize it inside your architecture — and stay on the hook for whether it actually works once we leave.
Get It Now
See Where Your AI Governance Gaps Are
We’ll map what your teams are actually running today — shadow tools included — then show you exactly where the gaps are and what closing them looks like.
- Map your current AI usage
- Review your governance and compliance gaps
- See the AGate control plane in action
- Scope a fixed-price readiness assessment
FAQ
Frequently Asked Questions
Straight answers to what decision-makers ask when evaluating an enterprise AI governance partner — scope, tooling, standards, and how Adastra compares.
No — tool licenses aren’t a governance framework. Whether AI creates value or risk comes down to who owns the use case, what controls apply before it ships, whether spend has an owner, and whether you can produce evidence when a regulator asks. We build that framework and enforce it in your environment. We don’t just describe it.
AGate is Adastra’s cost and access control plane, deployed inside your own tenant. It routes AI traffic through one governed layer, with single sign-on, role-based access, audit trails, spend budgets, and agent observability, so policy decisions actually reach production traffic instead of sitting in a document nobody checks against live usage.
Yes. Common starting points include a readiness assessment, a current-state gap review, an AGate deployment on its own, an AI registry and intake pilot, a Copilot or agent governance review, or an OSFI E-23 readiness check for federally regulated financial institutions. Most clients start with one narrow, fixed-price engagement, not the full program.
Big Four firms bring strong frameworks, assurance credibility, and board relationships, and we’re not arguing with that. Adastra differentiates by pairing that governance design with AGate’s deployable runtime controls, reusable accelerators, hyperscaler delivery experience, and hands-on data and AI engineering inside your environment — so the framework doesn’t stop at the document.
Our reference architecture maps AI governance controls to Microsoft Entra, Purview, Defender, Sentinel, Azure Monitor, Azure AI Foundry, Copilot Studio, and Agent 365 patterns. The exact mapping depends on your use cases, licensing, tenant architecture, and delivery model, so we confirm specifics during design instead of assuming one fit for everyone.
We connect them rather than replace them. Purview, ServiceNow, or your existing GRC platform can stay your system of record for policy and evidence, while AGate and our accelerators fill the gaps in AI traffic control, registry connection, evaluation, spend management, and adoption that most GRC tooling doesn’t reach.
Yes, and it isn’t limited to financial services. Financial institutions feel the strongest regulatory pressure right now, given OSFI E-23 and emerging US guidance, but the offer works just as well for any AI-active organization handling sensitive data, customer-impacting workflows, distributed AI usage, or spend and adoption questions it can’t yet answer.
Yes. Support covers a use-case and agent registry, risk classification, clear ownership, identity and access controls, prompt and output guardrails, tool and action permissions, monitoring, incident handling, runtime controls, kill switches, and cost management — all embedded wherever the agent actually runs and takes action.