Every AI Agent. Governed, Accountable, and Continuously Improving.
The Problem
Building agents is the easy part.
Companies are deploying AI agents across sales, operations, customer service, finance, and engineering. They are working, in isolation.
But no one can answer the basic questions: How many agents do we have running? What is each one doing? Who approved its behavior? Is it getting better or worse? What did it say to that customer last Tuesday? Who is responsible for it?
This is the spreadsheet era of AI — powerful capabilities deployed without infrastructure, governance, or visibility. For regulated industries, every ungoverned agent interaction is a potential audit finding. For every enterprise, it is an operational risk that compounds with every new agent deployed.
The Solution
Eight capabilities. One platform.
01
Agent Registry
Register, version, and own every AI agent across your organization — one source of truth for your entire AI workforce.
02
Skills & Knowledge
Domain experts author agent expertise directly in plain language. No engineering bottleneck. No prompt engineering required.
03
Connection Gateway
One MCP endpoint to every external system. Credentials managed centrally. Every call authorized, logged, and attributable.
04
Telemetry & Interaction Intelligence
Full interaction context with human outcome signals — accepted, edited, rejected — the ground truth no other platform captures.
05
Governance & Access Control
Role-based control with dual approval enforcement. No single stakeholder can change agent behavior alone.
06
Ethics & Policy Compliance
Instruction integrity scanning, semantic policy alignment, and continuous behavioral monitoring — three layers of protection.
07
Evaluation & Promotion Pipeline
Structured hard and soft gates, canary deployment, and automatic rollback. Every version proves itself before going live.
08
Governance UI
One console for every stakeholder — role-scoped access with the right information for each, from Platform Admin to general employee.
01
Agent Registry
Every agent. One source of truth.
Every AI agent in your organization — regardless of which LLM powers it — is registered, versioned, and owned. The registry tracks the full lifecycle: who built it, who approved it, what version is running, and what changed between versions. Rolling back to a prior version is a one-click operation with a full audit trail. Agents are managed assets, not scripts in a repo.
Why it matters
- Complete visibility into your entire AI workforce
- Immutable version history — every change attributed and timestamped
- One-click rollback with full audit trail
- Named business owner and engineering maintainer for every agent
02
Skills & Knowledge
Domain experts govern agent expertise directly.
Agent behavior comes from three distinct layers, each authored by the right person. Domain experts write skills — the business judgment that guides how agents think and decide, in plain language, no technical knowledge required. Operations teams write playbooks — the execution context that maps how your organization actually works. IT manages tool connections — the infrastructure agents use to interact with your systems. Each layer changes on its own cadence, without blocking the others.
Why it matters
- Business users update agent expertise without engineering bottleneck
- Skills versioned, auditable, and reusable across agents
- Operational playbooks stay current with how your org actually works
- Write instructions like you would coach a new hire — no prompt engineering
One connection. Every system. Complete control.
Most enterprises managing AI agents are managing dozens of individual connections, credentials, and configurations. Mashbot collapses that into a single governed endpoint — so your team spends time on outcomes, not infrastructure.
03
Connection Gateway
One connection to every system you run.
Managing individual MCP connections to every external platform — Salesforce, Snowflake, HubSpot, Slack, your internal APIs — is an operational burden that compounds with every new agent. The Connection Gateway eliminates it. Configure your platform connections once. Mashbot stores and manages credentials, handles OAuth token refresh and rotation, and proxies all tool calls through a single endpoint. Every agent uses one MCP connection. Every call is authorized, logged, and attributable.
Why it matters
- One MCP endpoint — Mashbot federates to all external systems
- Credentials managed centrally — agents never hold secrets
- Identity-aware authorization — role-based pre-flight checks on every call
- Complete action audit trail across every external system
04
Telemetry & Interaction Intelligence
Not just what happened. Why it happened.
Every interaction is logged with full context: who asked, which agent responded, what version was running, what tools it called, what documents it retrieved, and — critically — what the human did with the result. Accepted without change. Edited. Rejected. This outcome signal is the ground truth for continuous improvement. It tells you which skills to refine, which tool calls underperform, and which updates actually made things better. No external observability tool captures this because they never had the outcome data.
Why it matters
- Full interaction context — request, response, reasoning, tool calls, documents
- Human feedback loop — accepted, edited, rejected, with edit diffs captured
- Continuous improvement signal — the data tells you what to fix next
- Forensic capability — reconstruct any interaction exactly for any audit
05
Governance & Access Control
No behavior change ships without the right approvals.
Role-based control defines exactly who can change what. Business owners update skills. Operations teams update playbooks. Engineering maintains personas and model configuration. Compliance reviewers manage the policy corpus and clear flagged items. No single stakeholder can change agent behavior alone — the two-key principle ensures business expertise and engineering accountability are both present in every significant change. Every action produces an immutable audit record.
Why it matters
- Six roles covering every stakeholder from admin to general employee
- Two-key principle — neither business nor engineering can ship changes alone
- Full audit trail — who changed what, when, why, and who approved it
- Dual approval enforcement at the API level — not just in the UI
The data that tells you what to improve next.
External observability tools see API calls. Mashbot sees decisions — and what the human did with them. The accept, edit, reject signal is the ground truth for continuous improvement that no other platform captures.
Request Early Access06
Ethics & Policy Compliance
The platform watches whether agents are doing the right thing.
Governance controls who can change an agent. Eval tests whether it performs well. Neither answers the most important question: is this agent being instructed to do the right thing? The Ethics & Policy Compliance layer operates at three levels — instruction integrity on every save, semantic policy alignment review before deployment, and continuous behavioral monitoring after. It catches what access control allows through and what eval gates never anticipated.
Why it matters
- Instruction integrity scan on every save — catches violations before they enter the pipeline
- Semantic policy alignment — not keyword matching, actual understanding of intent
- Runtime behavioral monitoring — catches problems that emerge over hundreds of interactions
- Improves continuously across all customers — no single enterprise can build this alone
07
Evaluation & Promotion Pipeline
Prove it works before it goes live.
Every agent version passes through a structured promotion pipeline before reaching production. Hard gates block any version that fails on factual grounding, scope adherence, PII handling, escalation behavior, or policy compliance — no override path. Soft gates flag quality issues for documented human review. Canary deployment runs the new version alongside the current active version with automatic rollback if quality degrades. The entire record is attached to the version in the registry.
Why it matters
- Hard gates block non-compliant versions — no exceptions
- Canary deployment with automatic rollback on quality degradation
- Dual approval required for full promotion — Owner and Maintainer
- Every incident becomes a permanent regression test
08
Governance UI
One console. Every stakeholder. The right view for each.
The Governance UI surfaces the entire platform to every stakeholder at the right level of detail — from Platform Admin to general employee. Business owners refine skills and review performance. Compliance reviewers triage flagged items. Engineers manage versions and eval results. And general employees, the people interacting with agents every day, can report incidents and submit feedback directly. One navigation structure, role-scoped access, the right information for every person without the wrong information for any of them.
Why it matters
- Role-scoped access across six stakeholder types
- Employee Portal — anyone in the org can report incidents and submit feedback
- Every audit question answered in three clicks
- API and MCP access to telemetry — pipe it into your own analytics stack
Early Access
Shape the platform before anyone else.
We are working with a small number of founding customers whose requirements directly shape the platform. If your organization is building AI agents at scale and needs the governance infrastructure to match, we would like to talk.
Request Early AccessWhat founding customers receive
- Requirements prioritized in the platform build
- Founding customer commercial terms — locked for 3 years
- Direct access to the engineering team
- IP escrow for enterprise continuity assurance
- Shape the platform for your industry before anyone else