Collaborative AI Agent Governance for Regulated Industries
Ship AI Agents Faster. All Three Lines of Defence, Working in Concert.
Turn compliance into an operational layer inside your CI/CD pipeline. Automated checks,
immutable audit trails, and deployment-level accountability—moving at the speed of your AI systems.
Banking & Financial ServicesInsuranceHealthcareLegal & Professional Services
The Problem
Governance built for static software can't keep pace with living AI systems.
AI agents evolve through prompts, integrations, and workflows—often daily. Traditional governance
was never designed for this.
01
Compliance reviews happen too late
By the time Legal or Compliance review a workflow, Engineering has already changed it multiple times.
Policy and production diverge in silence.
02
No shared operational view
Engineering ships continuously. Compliance reviews quarterly. Product and Legal operate on entirely
different timelines with no common ground.
03
Accountability gaps surface at the worst time
When an incident or audit arrives, organizations struggle to prove explainability, approval history, or who
was accountable for a specific deployment.
How It Works
Governance that moves at the speed of deployment.
Concord embeds compliance directly into your AI delivery lifecycle—so oversight doesn't trail
behind, it moves with every push.
Automated Compliance Checks
Governance gates trigger automatically on every AI deployment. Compliance checks run inside the pipeline—no
manual review step, no bottleneck, no lag.
Shared Visibility Across Teams
Product, Engineering, Compliance, Legal, and Risk share a single operational view. Approvals, review
history, and workflow changes are visible to everyone who needs them.
Immutable Audit Trails
Every approval, change, and compliance decision is captured with a tamper-evident record. When an audit
arrives, you can prove exactly what ran, who approved it, and when.
CI/CD Pipeline Integration
Plug Concord directly into your deployment pipeline. Red-light / green-light governance gates, traceable
approvals, and AI-assisted legal review happen inside the workflow itself.
Pricing
Simple pricing. Serious governance.
Start free with one AI Agent. Expand as you deploy more. No per-seat fees—pricing scales with your
operational footprint.
Due to high demand from regulated enterprises, free trial onboarding is
managed on a first-come, first-served basis. Secure your priority placement today.
Security & Compliance
Our security obligation to every enterprise we serve.
We can't take on your regulatory obligations—but we give your risk and compliance teams the
architecture, controls, and audit evidence to satisfy them, including frameworks like OSFI's B-10 and B-13.
Isolated by Design
Every customer's data lives in its own database schema, enforced at the connection layer—so one tenant's
session can never reach another's data.
Defense in Depth
Every deployment passes automated dependency, code, container, and secret scanning, plus nightly
vulnerability testing, before it reaches production.
Provable Audit Trails
Every approval, change, and compliance decision is logged, with immutability maintained through
application-level controls that block edits or deletion.
Resilient by Default
Dual-zone failover, 30-day point-in-time recovery, and a ~15-minute recovery time objective keep the
platform available when it matters most.
The moments that make the case for operational governance.
Seven scenarios—regulatory and operational—that capture why AI governance can't live outside
the pipeline.
Contact centers, underwriting, marketing, and wealth management keep building agents faster than Model
Risk can track them. OSFI's finalized Guideline E-23 (Model Risk Management 2027) takes effect May 1,
2027, and will require federally regulated financial institutions to maintain an exhaustive, auditable
inventory of every model in production—including AI agents the business built or adopted, not just the
ones Model Risk signed off on.
The Concord pitch: Concord automatically discovers and maintains
an immutable registry of every AI agent entering staging or production, giving Model Risk visibility into
model lineage and changes well before May 2027 arrives.
Sections 12.1 and 65.2 of Quebec's private-sector privacy law apply whenever a decision affecting
someone—credit adjudication, insurance claim triage, benefits eligibility—is made exclusively by automated
processing. The business has to be able to produce the factors and parameters behind that specific
decision, on request.
The Concord pitch: Concord acts as the flight recorder. Whenever
an agent's decision logic, prompt, or underlying model changes, Concord captures the exact version,
parameters, and author—so a Law 25 disclosure request is a lookup, not a fire drill.
SOC 2's change-management criterion (CC8.1) and OSFI's Guideline B-13 both expect changes to be
authorized, tested, and approved before they reach production. AI agents drift through prompt edits, new
retrieval tools, and temperature changes that rarely go through the same review a code change would.
The Concord pitch: Concord turns prompt and model changes into
formal, tamper-evident change records with the sign-offs auditors already look for—Engineering and
Legal/Risk, before deployment.
Heads of AI and VPs of Digital Transformation keep hitting the same wall: engineering builds agents
faster than legal and risk can review them by hand. Every week an agent sits unlaunched is budget spent
and a harder conversation with an executive sponsor.
The Concord pitch: An async review console where Legal and Risk
read prompt diffs and run safety checks directly in the workflow—turning a review that took weeks into one
that takes days.
The meeting dragged on. Engineering grew frustrated—Compliance was "blocking innovation." Compliance grew
anxious—Engineering kept deploying systems they couldn't fully audit. The Chief Product Officer realized
the organization had accidentally built two separate operating systems: one for shipping software, one for
managing risk.
The problem wasn't incompetence. It was that compliance still operated like a quarterly legal review
process while AI systems were evolving daily through CI/CD pipelines. By the time Legal reviewed a
workflow, Engineering had changed it three times.
The insight: AI governance cannot survive as a PDF document. It
must become event-driven infrastructure—every deployment automatically triggering compliance checks, every
approval captured immutably inside the pipeline itself.
Engineering called the deployment successful. Product celebrated improved response times. Executives
referenced "AI transformation" in board meetings. But Compliance was never in the loop.
Compliance teams aren't struggling because they resist innovation—they're struggling because AI systems
evolve faster than traditional governance structures were designed to handle. By the time a quarterly
review happens, prompts have changed, integrations expanded, and autonomous behaviors shifted.
Engineering says: "We already tested the system." Compliance asks: "But who approved the operational
behavior?" Neither side is wrong. They're operating from different timelines.
The insight: Modern AI governance requires a shared operational
language between Product, Engineering, Compliance, Legal, and Risk—one that lives inside the CI/CD
pipeline, not in quarterly review meetings.
Today, AI systems recommend actions, route workflows, generate customer responses, summarize legal
matters, and trigger escalations. Yet most organizations govern these systems with fragmented
spreadsheets, disconnected approvals, and manual legal reviews.
Engineering ships. Compliance reviews later. Legal documents afterward. But AI agents don't wait for
quarterly governance meetings—they evolve continuously. Accountability becomes fragmented until an
incident forces the question no one can answer on the spot.
Customers want one thing from enterprises deploying AI: trust. And trust requires proof.
The insight: The organizations that can confidently answer "yes,
this system was governed responsibly" will define the next generation of trusted software companies in
regulated industries.
FAQ
Common questions.
An AI Agent is a distinct deployed agent, workflow, or autonomous AI system managed through
Concord—a customer service AI, document review workflow, escalation router, or any LLM-powered system in
production. Pricing is per-agent, not per user or seat.
Users who register with a valid company email address receive one AI Agent free for three
months. During the trial period, you'll have access to the platform's complete feature set, allowing you to
fully evaluate its capabilities before making a commitment. No credit card is required to start.
Traditional governance tools rely on static reviews, documentation, or periodic oversight.
Concord embeds governance directly into AI delivery workflows so approvals, compliance checks, auditability,
and accountability move at the same speed as deployment—not weeks behind it.
Yes. CI/CD integration is included in Professional and Enterprise tiers. Governance checks
and approval workflows embed directly into your deployment process, eliminating manual review bottlenecks
and improving end-to-end traceability across Engineering, Compliance, and Legal.
Yes. The pricing model supports a land-and-expand approach. Start with a single AI Agent,
validate internal governance workflows, then scale into Standard, Professional, or Enterprise as adoption
grows across your teams.
Enterprise is designed for organizations managing more than 20 AI Agents across multiple
teams and governance requirements. It includes everything in Professional, plus enterprise-grade
dashboarding, AI-assisted compliance oversight, and tailored commercial packaging with dedicated support and
custom SLAs.
Get Started
Ready to govern AI with confidence?
Start free with one AI Agent, or talk to us about
deploying Concord across your organization.