Agentic Orchestration Platform
by 
with 
glyphon (n.): the engraved mark that names a work's actors, decisions, and authority.
The control plane
for enterprise AI.
Glyphon coordinates teams of AI agents across cloud, on-premises, and air-gapped infrastructure, with the governance, audit, and human oversight that production and mission systems actually require. 56 specialized agents across 7 playbooks (6 production, 1 beta).
Why Glyphon exists
AI got capable. Running it in production did not get easier.
Every team now juggles many models across many providers, and rebuilds the same plumbing to make them safe: routing, approvals, logging, cost control. The intelligence is commoditized. The coordination is not.
Too many models
A different model is best for reasoning, coding, security, and vision, and the winner changes every quarter.
No shared governance
Policy, approvals, and access controls get re-implemented per project, inconsistently.
No audit trail
When an agent takes an action, there is rarely a tamper-evident record of what it did and who approved it.
Oversight bolted on late
Human-in-the-loop is an afterthought, not a property of the system that runs the work.
What it is
One layer between your AI and your infrastructure.
Glyphon is not a framework you wire by hand and not a chatbot. It is the coordination layer that decides which model runs each task, enforces policy, keeps a human in the loop, and records every action, the same way a control plane manages the machines underneath it.
Capabilities you compose
Environments it runs in
Binds capability to model
Declare the capability a step needs. Glyphon routes it to the right model, and you can swap the model without touching the workflow.
Coordinates the team
Agents run as a directed graph with parallel branches and a Team Lead that routes work and pauses for human decisions.
Records everything
A hash-chained log of every action and approval means the run can be replayed, audited, and trusted after the fact.
Model independence
You compose capabilities. Glyphon binds them to models.
Providers are an implementation detail. You design a workflow in terms of what each step needs to do, and the platform routes each step to the best available model for that job.
- Reasoning
- Coding
- Planning
- Security
- Compliance
- Documentation
- Research
- Vision
Resolve CVEs → verify build → document
Change the model row and the workflow above it never moves. That is what lets an orchestration stay stable as models change, so an accreditation is not re-opened on every release.
Collaboration & Control
Agents That Work Together, Humans That Stay in Charge
Agents collaborate in real-time through the Agent Mesh, requesting context and re-dispatching work through a central Team Lead. When decisions matter, the pipeline pauses and reaches humans via CLI, dashboard, email, Slack, SMS, or Teams, with every response tracked in hash-chained audit trails.
Agent Mesh
The Agent Mesh enables intelligent collaboration between agents. When an agent needs more data, it requests context from peers or asks the Team Lead to re-dispatch work, all within configurable budgets and safety boundaries.
Context Requests
Agents retrieve artifacts from prior pipeline stages on demand. No re-execution needed.
Re-dispatch
Agents request the Team Lead to re-run prior agents with additional context. Bounded by cost and count limits.
Bounded Agency
Agents reason freely. The system enforces limits: cost budgets, re-dispatch caps, cycle prevention.
Agent Executes
Pipeline runs the next agent in sequence
Trigger Detected
Safety, gate, or custom rule fires
Pipeline Pauses
Execution halts without losing state
Human Decides
Via CLI, dashboard, email, Slack, SMS, or Teams
Pipeline Resumes
Decision bound as a constraint
Decision Logged
Channel + identity tracked in audit trail
Agent Executes
Pipeline runs the next agent in sequence
Trigger Detected
Safety, gate, or custom rule fires
Pipeline Pauses
Execution halts without losing state
Human Decides
Via CLI, dashboard, email, Slack, SMS, or Teams
Pipeline Resumes
Decision bound as a constraint
Decision Logged
Channel + identity tracked in audit trail
Web dashboard escalation example at dashboard.glyphon.ai/escalations: CVE-2024-38816 detected on nginx:1.25-ubi9-minimal, step 5 of 11. Two remediation choices: Option A upgrade spring-webmvc to 6.1.13 (risk: Java 21 runtime change), Option B apply WAF mitigation (risk: partial fix only). Timeout: 8 minutes 42 seconds remaining. All decisions are logged to the immutable audit trail.
Deployment Tiers
Autonomous
Full automation for dev/test and low-risk workloads.
Supervised
Safety-triggered escalation for production environments.
Controlled
All triggers active for classified and mission-critical systems.
Approval Required
Every action requires human approval. Ideal for initial deployment.
Start at Approval Required to build trust, then relax to Supervised as confidence grows. Every decision fully auditable for ATO/RMF compliance, satisfying NIST SP 800-53 controls AU-2, AU-3, AU-8, AU-9, and AU-10 out of the box.
Deployment
The same workflow, wherever it has to run.
Glyphon is self-hosted inside your authorization boundary. The workflow you build on a laptop is the workflow that runs in the enclave. Only the execution environment changes.
- Developer workstation
- Enterprise datacenter
- Commercial cloud
- GovCloud
- Air-gapped enclave
- Fully local execution · roadmap
STIG-hardened Iron Bank containers from registry1.dso.mil. Three deployment tiers, from local HTTPS to Iron Bank, on Kubernetes, ECS, Fargate, OpenShift, or an air-gapped network.
Playbook library
Defensive cyber, delivered as production playbooks
Glyphon does not hand you a blank canvas. It ships a library of playbooks, 56 agents across 7 (6 production, 1 beta), each a repeatable workflow that produces a concrete security outcome for enterprise and government alike. Not demos, deliverables.
Find and fix vulnerabilities
Trivy · 15 agents
productionCVE Resolution
Resolve container image CVEs through dependency upgrades, with rebuild verification and compliance-ready documentation.
Semgrep · 8 agents
productionSemgrep Remediation
Find and fix real source-code vulnerabilities with test-validated edits. Automated triage separates fixable findings from false positives.
Harden and benchmark
Trivy + CIS · 7 agents
productionContainer Hardening
Harden Dockerfiles to CIS Docker Benchmark standards, with a rebuild and smoke test after every fix.
OpenSCAP + PowerSTIG · 9 agents
productionAMI Hardening
Scan and STIG-harden machine images across 6 OS platforms: Windows, Amazon Linux 2 and 2023, RHEL 8 and 9.
Assess and produce evidence
Multi-Scanner · 7 agents
productionSecurity Posture
Unified view across SAST scanners with cross-tool deduplication, NIST SP 800-53 mapping, and executive-ready posture reports.
eMASS API · 5 agents
productioneMASS Submission
Generate POA&M reports and eMASS export packages from assessment results. Chains after any scan playbook.
FedRAMP + NIST · 5 agents
betaSSP Generator
Draft FedRAMP System Security Plans from deterministic control data, with LLM review reserved for gap analysis only.
Verified remediation
Nothing ships that breaks the build.
The risk with automated fixes is not finding them, it is shipping one that quietly breaks the system. Glyphon proves every change against a baseline before it counts: the startup smoketest re-runs after every fix, and CVE resolution re-scans the image so a finding has to be gone, not just suppressed.
Step 01
Capture a baseline
Before any action, STIG, or remediation, Glyphon records a successful-startup baseline: the application boots, or the OS image boots clean.
Step 02
Smoketest every change
Each individual change is applied and smoketested against that baseline, so a regression is caught at the change that caused it.
Step 03
Roll back and document
A deviation from baseline, such as a failed startup, has that remediation removed, documented, and written into a POA&M. The system stays working, the gap stays visible.
Governance
Governance is the product, not a setting.
These are not features you switch on. In the environments Glyphon targets, they are the requirements that decide whether AI is allowed to run at all.
Immutable audit trail
Hash-chained JSONL. Every action and human decision links to the previous entry by SHA-256, so tampering is detectable on verification.
Human approval
Policy-triggered escalation to a real person across six channels: CLI, dashboard, email, Slack, SMS, or Teams, with full attribution recorded.
Policy enforcement
Oversight tiers per workload, from fully autonomous to approval-required, set by classification and risk.
Cost accounting
Per-run, per-agent, per-model cost visibility, so spend is a number you can govern, not a surprise.
Observability
Trace every agent run and model call. Langfuse for commercial customers, OpenTelemetry and Grafana for air-gapped and government deployments.
Replay and lineage
Any run can be reconstructed from its log, for review, incident analysis, or accreditation evidence.
Proof
Run against real systems. Measured in real numbers.
The story is the platform. The evidence is that it already does the work, on real targets, at costs you can check.
# the same playbook, any provider, no rewrite
$ glyphon run --playbook ./trivy --project ./app --model gpt-4o --multi-pass 3
Pass 1: 142 CVEs → 96 resolved (68%)
Pass 2: 46 CVEs → 18 resolved (39%)
Pass 3: 28 CVEs → 5 resolved (converging)
Result: 119 of 142 resolved (84%) | Cost: $6.41 | $0.05/CVE
# OWASP juice-shop lab benchmark, Azure GPT-4o (CVE counts vary by image tag and scan date)Also proven: container hardening to CIS benchmarks, SAST remediation with test-validated edits, and AMI STIG hardening across six operating systems. On government-aligned inference paths, Maverick on AWS Bedrock GovCloud has delivered up to 15x lower cost than commercial baselines on the same playbooks. The five DoD systems above were assessed and remediated by Accelera Solutions: Glyphon did the work, but the resulting security posture belongs to those systems, not to the platform.
Full deployment results and government procurement details →
Roadmap
Built for where AI operations are going.
Direction, not today's shipping capability. The architecture is designed to absorb each of these without changing the workflows you already run.
Local model execution
Run capable models fully on-premise or on-device, no provider connection required.
GPU-aware scheduling
Place work by available accelerators across the fleet.
Model + capability registry
A governed catalog of approved models and the capabilities they satisfy.
Evaluation pipelines
Score and gate models before they are allowed into a workflow.
Model lifecycle
The AI supply chain: evaluate, approve, deploy, monitor, retire, as one governed loop.
Cyber-specialized models
Local, mission-tuned models for security and defensive operations.
IV Engage the platform
Built by Accelera Solutions and SigilArk
with Glyphon is the agentic orchestration platform Accelera Solutions and its SigilArk affiliate use to accelerate security remediation and RMF evidence on federal engagements. Self-hostable and deployed inside your authorization boundary as part of the engagement.
Engage Accelera Solutions to bring Glyphon to your program. SigilArk is Accelera's small-business affiliate.
Accelera Solutions is the point of contact on all contracts.
Engagements scoped program by program, aligned to your authorization path.
Get Started
Ready to Orchestrate?
Schedule a capability briefing or request a technical demonstration to see how agentic orchestration can work for your security, compliance, and DevSecOps workflows.
Perpetual license to the major version, minor updates and patch cycles included. Delivered and supported through Accelera Solutions, with SigilArk.