THE PLATFORM

Give every engineer extraordinary enablement.

GalentAI builds a living context graph of your systems, then governs every prompt, agent and output against it. It sits over the tools your teams already use and runs in your own cloud, with Forward-Deployed Engineers taking it from pilot to defensible production.
REQUEST a DEMO

Built for the enterprise, not the individual

Knowledge that stays in your cloud. Governance by default. Every decision explainable. A governed sandbox, live in days.

Built for the enterprise

Governs delivery across every team, role and system. Not a productivity tool for one developer.

The graph is your IP

Tribal knowledge encoded, reusable, and stored in your infrastructure, not ours.

Governance built in

Auditable, traceable and explainable by architecture.

Reads before it acts

Every agent works from a context graph of your real systems, not a guess from one repository.

Sits on your stack

Cursor, Copilot, Claude Code, your Jira. Unified without replacing a tool or a team.

Live, like a mirror

Adoption, velocity, quality and cost. Every number tied to a named owner in real time.
Platform architecture

Inside GalentAI.
The full stack.

Eight layers, from the developer workbench down to model routing, that usually come from eight vendors. In GalentAI they share one context graph and one audit trail.
Already using Claude Code, Cursor, Copilot or Kiro? Keep them. Galent layers governance and context over the tools your devs already love.
DEVELOPER SURFACE
4 components · 5 tools
Experience & Workbench
Agent Orchestration & Harness
Core AI Agents
GalentAI Gateway
Knowledge & Context Graphs
Governance & Traceability
Auth, Identity & Multi-Tenancy
CI/CD, Support and SRE
LAYER 01 / 08

Experience & Workbench

Where engineers, architects and business users work with GalentAI: build agents, modernize legacy code and see results by role
Agent Builder Studio
Visual drag-and-drop interface for building and deploying AI agents.
Modernization Workbench
Codebase analysis, reverse engineering and migration planning for legacy estates, proven across 50+ modernization programs.
Coding Agent
Context-aware AI assistant, governed by the Context Graph at every step.
Generative UI & Dashboards
Role-based dashboards auto-generated per persona.
Executive Dashboard
Adoption, velocity, quality and cost, live, with every numbertied to a named owner.
WORKS WITH:
vscode
JETBRAINS
cursor
CLAUDE CODE
kiro
github
COPILOT
LAYER 02 / 08

Agent Orchestration & Harness

The execution core. Coordinates agents, manages memory, enforces human-in-the loop gates and routes each call to the right model.
Orchestration Engine + DAG
Plans and executes multi-step agent workflows as DAGs.
Agent Harness
Sovereign intermediary between apps and LLMs, controls what context each model sees.
Context Graph Runtime
Live query engine retrieving governing rules at 45ms P95.
HITL Review Gate
Blocks downstream execution until human approval at defined points.
Agent Memory
Session and long-term memory, scoped per tenant and per agent.
TOOLS:
PYTHON
FASTAPI
REDIS
LANGGRAPH
TEMPORAL
LAYER 03 / 08

Core AI Agents

175+ reusable agents across the SDLC. Four core agents do most of the work; each runs in a bounded scope, and the Critic checks every output before a human sees it.
Spec Agent
Generates features, epics, stories, criteria, and NFRs. Pushes to Jira.
Analyzer Agent
Deep codebase analysis: AST parsing, dependency graphing, hot paths.
Codegen Agent
Generates code in bounded MicroPrompts (<2,000 tokens).
Critic Agent
Reviews AI code against architectural and security policy before human review.
Test Agent
Writes unit, regression and contract tests.
Migration Agent
Converts legacy code and data safely.
RCA Agent
Finds root cause through the RCM Engine.
Documentation Agent
Generates docs from code and decisions.
Business Agents
Clears claims, invoice exceptions and sales handoffs
OBSERVED WITH
langfuse
opentelemetry
LAYER 04 / 08

GalentAI Gateway

Routes every request to the right model. Manages cost, limits, PII redaction, fallbacks.
Model Router
Selects the optimal LLM per task by capability, cost, latency, and approved list.
Canonical Prompt Library
Versioned, tested prompt templates that eliminate drift.
Policy Engine & Guardrails
Enforces content and compliance constraints before any prompt reaches an LLM.
PII Redaction & DLP
Automatically redacts PII before LLM calls.
MCP Gateway
Every MCP tool call passes the same policy, redaction and logging as a model call.
Cost & Quota Controls
Budgets per team, agent and model, with alerts before limits are hit.
TOOLS:
claude
openai
gemini
aws bedrock
AZURE AI FOUNDRY
GOOGLE VERTEX AI
LLAMA
MISTRAL
LAYER 05 / 08

Knowledge & Context Graphs

Persistent institutional intelligence. The Knowledge Graph maps what exists; the Context Graph governs what should happen.
Knowledge Graph
Living map of your system: code, APIs, databases, logsand tickets. It belongs to you.
Context Graph: Your IP
Your governing constitution as machine-readable rules, in your environment.
RAG Pipeline
Retrieval-augmented generation.
Artifact Store
Immutable storage for specs, code, tests, audit trails.
TOOLS:
mongodb atlas
neo4j
POSTGRESQL (PGVECTOR)
redis
pinecone
Amazon Bedrock
LAYER 06 / 08

Governance & Traceability

Every AI decision captured, explained, and defensible to any regulator or board.
Traceability Matrix
Full provenance: what / why / who / when / against which rule. Immutable.
Governance & Policy
Controls mapped to SOX, HIPAA, PCI-DSS, NIST and the EU AI Act, enforced at every stage.
Audit Trail
Tamper-evident log of every agent action, decision, and model call.
SIEM Integration
Streams audit events to Splunk, Sentinel, or your existing SIEM.
Evaluation & Red-Teaming
Agents are tested against adversarial prompts andpolicy regressions before every release.
TOOLS:
SPLUNK
SENTINEL
datadog
elastic
 GOOGLE SECOPS
OPENTELEMETRY
LAYER 07 / 08

Auth, Identity & Multi-Tenancy

Enterprise-grade identity, access control, and tenant isolation.
Auth Adapter Layer
Federated enterprise login across Auth0, Okta, Entra, Ping.
RBAC / ABAC
Every user, agent, and service precisely scoped.
Tenant Resolver
Complete data isolation between tenants.
License & Metering
Usage metering and quota management by team, agent and tenant.
TOOLS:
AUTH0(zero)
OKTA
ENTRA
PING IDENTITY
LAYER 08 / 08

CI/CD, Support and SRE

Infrastructure and operational layer, deployed inside your cloud with your toolchain.
CDKTF Multi-Cloud IaC
Reproducible, auditable deployments across AWS, Azure, GCP, on-prem.
Helm / Kubernetes
GalentAI deploys as Kubernetes workloads in your cluster.
OpenObserve / Langfuse
Distributed traces, metrics, and LLM-specific monitoring.
CI/CD Pipelines
Integrates with Jenkins, ArgoCD, GitHub Actions.
RCM Engine
Root-cause analysis on incidents, linked back to the change that caused them.
TOOLS:
KUBERNETES
HELM
DOCKER
TERRAFORM
ARGO CD
GITHUB ACTIONS
JENKINS
DEVELOPER SURFACE
4 components · 5 tools
Experience & Workbench
Accordian Arrow
LAYER 01 / 08

Experience & Workbench

Where engineers, architects and business users work with GalentAI: build agents, modernize legacy code and see results by role
Agent Builder Studio
Visual drag-and-drop interface for building and deploying AI agents.
Modernization Workbench
Codebase analysis, reverse engineering and migration planning for legacy estates, proven across 50+ modernization programs.
Coding Agent
Context-aware AI assistant, governed by the Context Graph at every step.
Generative UI & Dashboards
Role-based dashboards auto-generated per persona.
Executive Dashboard
Adoption, velocity, quality and cost, live, with every numbertied to a named owner.
WORKS WITH:
vscode
JETBRAINS
cursor
CLAUDE CODE
kiro
github
COPILOT
Agent Orchestration & Harness
Accordian Arrow
LAYER 02 / 08

Agent Orchestration & Harness

The execution core. Coordinates agents, manages memory, enforces human-in-the loop gates and routes each call to the right model.
Orchestration Engine + DAG
Plans and executes multi-step agent workflows as DAGs.
Agent Harness
Sovereign intermediary between apps and LLMs, controls what context each model sees.
Context Graph Runtime
Live query engine retrieving governing rules at 45ms P95.
HITL Review Gate
Blocks downstream execution until human approval at defined points.
Agent Memory
Session and long-term memory, scoped per tenant and per agent.
TOOLS:
PYTHON
FASTAPI
REDIS
LANGGRAPH
TEMPORAL
Core AI Agents
Accordian Arrow
LAYER 03 / 08

Core AI Agents

175+ reusable agents across the SDLC. Four core agents do most of the work; each runs in a bounded scope, and the Critic checks every output before a human sees it.
Spec Agent
Generates features, epics, stories, criteria, and NFRs. Pushes to Jira.
Analyzer Agent
Deep codebase analysis: AST parsing, dependency graphing, hot paths.
Codegen Agent
Generates code in bounded MicroPrompts (<2,000 tokens).
Critic Agent
Reviews AI code against architectural and security policy before human review.
Test Agent
Writes unit, regression and contract tests.
Migration Agent
Converts legacy code and data safely.
RCA Agent
Finds root cause through the RCM Engine.
Documentation Agent
Generates docs from code and decisions.
Business Agents
Clears claims, invoice exceptions and sales handoffs
OBSERVED WITH
langfuse
opentelemetry
Galent AI Gateway
Accordian Arrow
LAYER 04 / 08

Galent AI Gateway

Routes every request to the right model. Manages cost, limits, PII redaction, fallbacks.
Model Router
Selects the optimal LLM per task by capability, cost, latency, and approved list.
Canonical Prompt Library
Versioned, tested prompt templates that eliminate drift.
Policy Engine & Guardrails
Enforces content and compliance constraints before any prompt reaches an LLM.
PII Redaction & DLP
Automatically redacts PII before LLM calls.
MCP Gateway
Every MCP tool call passes the same policy, redaction and logging as a model call.
Cost & Quota Controls
Budgets per team, agent and model, with alerts before limits are hit.
TOOLS:
claude
openai
gemini
aws bedrock
AZURE AI FOUNDRY
GOOGLE VERTEX AI
LLAMA
MISTRAL
Knowledge & Context Graphs
Accordian Arrow
LAYER 05 / 08

Knowledge & Context Graphs

Persistent institutional intelligence. The Knowledge Graph maps what exists; the Context Graph governs what should happen.
Knowledge Graph
Living map of your system: code, APIs, databases, logsand tickets. It belongs to you.
Context Graph: Your IP
Your governing constitution as machine-readable rules, in your environment.
RAG Pipeline
Retrieval-augmented generation.
Artifact Store
Immutable storage for specs, code, tests, audit trails.
TOOLS:
mongodb atlas
neo4j
POSTGRESQL (PGVECTOR)
redis
pinecone
Amazon Bedrock
Governance & Traceability
Accordian Arrow
LAYER 06 / 08

Governance & Traceability

Every AI decision captured, explained, and defensible to any regulator or board.
Traceability Matrix
Full provenance: what / why / who / when / against which rule. Immutable.
Governance & Policy
Controls mapped to SOX, HIPAA, PCI-DSS, NIST and the EU AI Act, enforced at every stage.
Audit Trail
Tamper-evident log of every agent action, decision, and model call.
SIEM Integration
Streams audit events to Splunk, Sentinel, or your existing SIEM.
Evaluation & Red-Teaming
Agents are tested against adversarial prompts andpolicy regressions before every release.
TOOLS:
SPLUNK
SENTINEL
datadog
elastic
 GOOGLE SECOPS
OPENTELEMETRY
Auth, Identity & Multi-Tenancy
Accordian Arrow
LAYER 07 / 08

Auth, Identity & Multi-Tenancy

Enterprise-grade identity, access control, and tenant isolation.
Auth Adapter Layer
Federated enterprise login across Auth0, Okta, Entra, Ping.
RBAC / ABAC
Every user, agent, and service precisely scoped.
Tenant Resolver
Complete data isolation between tenants.
License & Metering
Usage metering and quota management by team, agent and tenant.
TOOLS:
AUTH0(zero)
OKTA
ENTRA
PING IDENTITY
CI/CD, Support and SRE
Accordian Arrow
LAYER 08 / 08

CI/CD, Support and SRE

Infrastructure and operational layer, deployed inside your cloud with your toolchain.
CDKTF Multi-Cloud IaC
Reproducible, auditable deployments across AWS, Azure, GCP, on-prem.
Helm / Kubernetes
GalentAI deploys as Kubernetes workloads in your cluster.
OpenObserve / Langfuse
Distributed traces, metrics, and LLM-specific monitoring.
CI/CD Pipelines
Integrates with Jenkins, ArgoCD, GitHub Actions.
RCM Engine
Root-cause analysis on incidents, linked back to the change that caused them.
TOOLS:
KUBERNETES
HELM
DOCKER
TERRAFORM
ARGO CD
GITHUB ACTIONS
JENKINS

Integrations & connectors

1,100+ integrations · 26 categories

Results 1

Showing items 1 to3 of 6

SOURCE CONTROL & CI/CD
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0
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GitHub
SOURCE CONTROL & CI/CD
GitLab
SOURCE CONTROL & CI/CD
Bitbucket
SOURCE CONTROL & CI/CD
Azure DevOps
SOURCE CONTROL & CI/CD
GitHub Actions
SOURCE CONTROL & CI/CD
Jenkins
SOURCE CONTROL & CI/CD
Argo CD
SOURCE CONTROL & CI/CD
CircleCI
SOURCE CONTROL & CI/CD
Harness
SOURCE CONTROL & CI/CD
Buddy
SOURCE CONTROL & CI/CD
Drone CI
SOURCE CONTROL & CI/CD
GoCD
SOURCE CONTROL & CI/CD
JFrog Artifactory
SOURCE CONTROL & CI/CD
Sonatype Nexus
SOURCE CONTROL & CI/CD
TeamCity
SOURCE CONTROL & CI/CD
Tekton
SOURCE CONTROL & CI/CD
AWS CodePipeline
SOURCE CONTROL & CI/CD
VS Code
IDE & AI CODING
JetBrains
IDE & AI CODING
Cursor
IDE & AI CODING
GitHub Copilot
IDE & AI CODING
Claude Code
IDE & AI CODING
Kiro
IDE & AI CODING
Windsurf
IDE & AI CODING
Amazon Q Developer
IDE & AI CODING
Tricentis Tosca
Testing & Quality
qTest
Testing & Quality
Selenium
Testing & Quality
Playwright
Testing & Quality
Cypress
Testing & Quality
JMeter
Testing & Quality
k6
Testing & Quality
BrowserStack
Testing & Quality
Sauce Labs
Testing & Quality
SonarQube
Testing & Quality
ServiceNow ITSM and CMDB
ITSM & CMDB
BMC Helix
ITSM & CMDB
Jira Service Management
ITSM & CMDB
Ivanti Neurons
ITSM & CMDB
Freshservice
ITSM & CMDB
ManageEngine ServiceDesk Plus
ITSM & CMDB
TOPdesk
ITSM & CMDB
PagerDuty
INCIDENT & ON-CALL
Opsgenie
INCIDENT & ON-CALL
xMatters
INCIDENT & ON-CALL
Splunk On-Call
INCIDENT & ON-CALL
incident.io
INCIDENT & ON-CALL
FireHydrant
INCIDENT & ON-CALL
Rootly
INCIDENT & ON-CALL
Grafana OnCall
INCIDENT & ON-CALL
BigPanda
INCIDENT & ON-CALL
Datadog
OBSERVABILITY & MONITORING
Dynatrace
OBSERVABILITY & MONITORING
New Relic
OBSERVABILITY & MONITORING
Splunk Observability
OBSERVABILITY & MONITORING
AppDynamics
OBSERVABILITY & MONITORING
Grafana
OBSERVABILITY & MONITORING
Prometheus
OBSERVABILITY & MONITORING
Elastic
OBSERVABILITY & MONITORING
OpenTelemetry
OBSERVABILITY & MONITORING
OpenObserve
OBSERVABILITY & MONITORING
Amazon CloudWatch
OBSERVABILITY & MONITORING
Azure Monitor
OBSERVABILITY & MONITORING
ThousandEyes
OBSERVABILITY & MONITORING
Nexthink
OBSERVABILITY & MONITORING
Microsoft Sentinel
SECURITY
Splunk Enterprise Security
SECURITY
Google SecOps
SECURITY
CrowdStrike Falcon
SECURITY
Cortex XSOAR
SECURITY
Snyk
SECURITY
Checkmarx
SECURITY
Veracode
SECURITY
Wiz
SECURITY
Prisma Cloud
SECURITY
FortiSIEM
SECURITY
HashiCorp Vault
SECURITY
Tenable
SECURITY
Qualys
SECURITY
Okta
IDENTITY & ACCESS
Microsoft Entra ID
IDENTITY & ACCESS
Auth0
IDENTITY & ACCESS
Ping Identity
IDENTITY & ACCESS
CyberArk
IDENTITY & ACCESS
SailPoint
IDENTITY & ACCESS
OneLogin
IDENTITY & ACCESS
AWS IAM
IDENTITY & ACCESS
Keycloak
IDENTITY & ACCESS
AWS
CLOUD & INFRASTRUCTURE
Microsoft Azure
CLOUD & INFRASTRUCTURE
Google Cloud
CLOUD & INFRASTRUCTURE
Oracle Cloud
CLOUD & INFRASTRUCTURE
VMware
CLOUD & INFRASTRUCTURE
Red Hat OpenShift
CLOUD & INFRASTRUCTURE
Kubernetes
CLOUD & INFRASTRUCTURE
Docker
CLOUD & INFRASTRUCTURE
Helm
CLOUD & INFRASTRUCTURE
Terraform
CLOUD & INFRASTRUCTURE
CDKTF
CLOUD & INFRASTRUCTURE
Ansible Automation Platform
CLOUD & INFRASTRUCTURE
Thank you! Your submission has been received!
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What you keep when the project ends.

Same project, five ways to run it. With four of them, the value leaves when the project ends. With GalentAI, the platform, the graph and the agents stay.
capability
FULL SDLC COVERAGE
DEPLOYED IN YOUR VPC
CONTEXT GRAPH IN YOUR CLOUD OR ON-PREM
INSTITUTIONAL MEMORY
GOVERNANCE AND FULL AUDIT
explainability
MODEL AGNOSTIC
What you own at end
GALENTAI
End to end
checkmark
From Day One
checkmark
Your institutional intelligence, permanent in your environment
checkmark
Knowledge Graph, updated every commit
checkmark
Mapped to SOX, HIPAA, PCI-DSS, EU AI Act
checkmark
Every decision: what, why, who, when
checkmark
Any LLM, swappable anytime
checkmark
Software + graphs + agents + audit trail
checkmark
CURSOR / COPILOT
IDE only
Restricted Options
-/-
Session only
Tool logs only
-/-
Ecosystem-tied
Faster output
DEVIN / COGNITION
Partial
Enterprise option
-/-
Session only
Audit logs
-/-
Multi-cloud
Faster output
TALENT MARKETS
Client’s problem
-/-
-/-
People walk out
Left to client
-/-
-/-
Headcount dependency
CONSULTING
Via billed hours
Project by Project
Leaves with the contractors
Leaves with the firm
Via methodology
On request
Varies
Deliverables only
compliance & trust

Answers for your auditors,  not just your engineers.

Governance ships pre-mapped to the regulatory and security frameworks you already answer to. Every control can be enforced on agent input, output or both, and every decision is logged to your SIEM.
POLICY FRAMEWORKS MAPPED TO
GDPR
EU AI Act
NIST AI RMF
SOC 2
HIPAA
HITRUST
FCA
PSD2
FINRA
SOX
DPDP LAW
MITRE ATLAS
ISO 27001/42001
PCI-DSS
+
CCPA
COPPA
DORA
FERPA
GLBA
NIST CSF
NYDFS
ENFORCEMENT MODES
Advisory
Log it but let it through
Monitor
Alert, annotate, and continue
Block
Halt it at the gate
AUDIT EVENTS STREAM TO YOUR SIEM
Splunk HEC
Elastic
Datadog
Chronicle
Sumo Logic
Cortex
FortiSIEM
OTLP / Syslog
ENABLEMENT LAYER

Every prompt enriched. Every action governed. Every decision explained

GalentAI sits between your engineers, your agents and any AI model. Every promptpicks up your context, passes your rules and leaves an audit trail before a model ever sees it.
FOR ENGINEERS
FOR BUSINESS TEAMS
ONE LAYER FOR BOTH
sdlc inputs
A developer asks
Describe a feature, a bug or a refactor in plain language or a spec. No context-pasting, no prompt engineering.
NATURAL LANGUAGE
spec
story
sdlc inputs
Your coding agent calls in.
Cursor, Copilot or Claude Code sends a request. GalentAI adds the context the IDE cannot see.
CURSOR
vs code
COPILOT
CLAUDE CODE
sdlc inputs
The pipeline calls in.
A Jira epic, a sprint plan or a CI/CD event starts work automatically.
JIRA EPIC
SPRINT
CI/CD
Galent Enablement Layer
Knowledge Graph
A living, queryable map of your entire system: source code (AST parsed), APIs, databases, logs, ITSM tickets, and tribal knowledge. Built before any AI acts and continuously updated.
ast PARSING OF ALL SOURCE CODE
DEPENDENCY & API MAPPING
ITSM/TICKET/DOC INGESTION
45MS P95 CONTEXT RETRIEVAL
context graph
Your governing constitution encoded as machine-readable, enforceable rules — architectural principles, compliance policies, business logic, coding standards. It lives inside your four walls and gets smarter with every sprint.
Architectural principle encoding
Compliance rule enforcement
Business logic as policy
Decision trace per action
SPEC-DRIVEN DEVELOPMENT
No code is generated without a verified plan. Features, epics, stories, acceptance criteria, and NFRs are created in Jira before any code generation.
Feature → Epic → Story → Points
Acceptance criteria auto-generated
NFRs embedded in every epic
FDE review gate on every spec
4-MODE CLASSIFICATION
Every task classified before work starts: Fully AI / AI + Human Validation / Human-Led + AI Validation / Fully Human. The human-to-AI ratio is agreed upfront, embedded in the plan, and enforced throughout.
Mode 1: Fully AI
Mode 2: AI generates, human approves
Mode 3: Human leads, AI validates
Mode 4: Fully human
GOVERNANCE & EXPLAINABILITY
Every AI decision has a full audit trail: what, why, by whom, against which rule, and when. SOX, HIPAA, PCI-DSS, EU AI Act compliant by design.
What: action and output
Why: reasoning trace
Who: agent + human + rule
When: immutable timestamp
sdlc outputs
A pull request your reviewers can trust
Spec-verified, rule-checked code pushed to your repo, with the reasoning attached.
github/gitlab
PR
review queue
sdlc outputs
A backlog ready for sprint planning
Epics, stories, acceptance criteria, NFRs and points, pushed to Jira, Azure DevOps or Linear.
jira
azure devops
linear
sdlc outputs
Tests and a permanent trail
Regression tests generated with the code, plus a Traceability Matrix entry that cannot be edited later.
test harness
traceability
splunk
AGENT INPUTS
A live event
A claim is submitted, an invoice is flagged, a KYC file is escalated. The agent picks it up the moment an analyst would.
Claims
Invoice exception
KYC Escalation
AGENT INPUTS
Someone asks
A business user asks a question or requests an action in plain language. No ticket, no waiting on IT, no spreadsheet export.
Natural Language
Dashboard
API
AGENT INPUTS
A system changes state.
SAP, Salesforce or your ITSM fires an event,and the agent acts on the same signal your team watches.
SAP/Oracle
Salesforce
Webhook
Galent Enablement Layer
Knowledge Graph
A living map of your business: customers, products, transactions and the rules that govern them, read from your systems of record.
CUSTOMER, POLICY & CLAIM ENTITIES
BUSINESS RULES AS POLICY
SYSTEM-OF-RECORD LINKS
PROCESS HISTORY
100% SECURED IN SANDBOX
context graph
Your governing constitution encoded as machine-readable, enforceable rules — architectural principles, compliance policies, business logic, coding standards. It lives inside your four walls and gets smarter with every sprint.
Architectural principle encoding
Compliance rule enforcement
Business logic as policy
Decision trace per action
Policy Engine
Enforces business rules, architectural standards, and compliance constraints before any prompt reaches an LLM. PII redaction, rate limiting, token metering, and fallback circuit breakers.
PII redaction before LLM calls
Rate limiting per user and agent
Token metering
Fallback / circuit breaker
GOVERNANCE & EXPLAINABILITY
Every AI decision has a full audit trail: what, why, by whom, against which rule, and when. SOX, HIPAA, PCI-DSS, EU AI Act compliant by design.
What: action and output
Why: reasoning trace
Who: agent + human + rule
When: immutable timestamp
4-MODE CLASSIFICATION
Every task classified before work starts: Fully AI / AI + Human Validation / Human-Led + AI Validation / Fully Human. The human-to-AI ratio is agreed upfront, embedded in the plan, and enforced throughout.
Mode 1: Fully AI
Mode 2: AI generates, human approves
Mode 3: Human leads, AI validates
Mode 4: Fully human
AGENT outPUTS
Same rules, every time
Every decision is checked against the same business rules, whichever agent, shift or region handled it. Analyst-to-analyst variance dropsout of the process.
Decision Record
Approval Flow
AGENT outPUTS
Written back, with the reason
Approved output goes back to the system of record with its provenance attached, so the next person sees what changed and under which rule.
ERP/SAP
Salesforce
AGENT outPUTS
An audit trail in plain English
What happened, which rule applied, who or what approved it and when. Ready for an auditor on demand, not rebuilt after the fact.
Board Dashboard
Compliance
Live production trigger
A business function, not a demo.
A real event fires in production: a claim, an invoiceexception, a code change. Before any model is called, the Control Plane decides which LLMmay handle it, under which policy, and whether a human must be in the loop.
Claim/ticket
Code request
KYC event
Bounded at design time
Scope set at design time
Which systems, fields and decisions an agent may touch isfixed before runtime, not discovered by the model on the fly. Nothing happens outside thatscope.
System scope
Field-level rules
Decision limits
Same layer, every persona
Developer, analyst or agent
A coding request and a live business decision passthrough the same layer: one policy engine, one audit trail, one set of human checkpoints.
IDE
Workbench
API
GalentAI Control Plane
Unified Knowledge Graph
A living, queryable map of your entire system: source code (AST parsed), APIs, databases, logs, ITSM tickets, and tribal knowledge. Built before any AI acts and continuously updated.
CUSTOMER
POLICY & CLAIM ENTITIES
BUSINESS RULES AS POLICY
SYSTEM-OF-RECORD LINKS
PROCESS HISTORY
100% SECURED IN SANDBOX
context graph
Your governing constitution encoded as machine-readable, enforceable rules — architectural principles, compliance policies, business logic, coding standards. It lives inside your four walls and gets smarter with every sprint.
Architectural principle encoding
Compliance rule enforcement
Business logic as policy
Decision trace per action
Control Plane
A design-time layer that fixes, for every task class, which model may be called, what it is authorized to touch, and which decisions require a human — before any agent runs in production. Nothing is decided by the model at runtime; it is decided about the model, upfront, and enforced every time it acts.
Model routing fixed per task, not per prompt
No new fields, records, or data created outside scope
Every decision documented: rule, model, human, timestamp
Swap LLMs without changing governed behavior
4-Mode Human-AI
Every task classified before work starts: Fully AI / AI + Human Validation / Human-Led + AI Validation / Fully Human. The human-to-AI ratio is agreed upfront, embedded in the plan, and enforced throughout.
Mode 1: Fully AI
Mode 2: AI generates, human approves
Mode 3: Human leads, AI validates
Mode 4: Fully human
Unified Audit Trail
Every AI decision has a full audit trail: what, why, by whom, against which rule, and when. SOX, HIPAA, PCI-DSS, EU AI Act compliant by design.
What: action and output
Why: reasoning trace
Who: agent + human + rule
When: immutable timestamp
No runtime guesswork
Swap the model, keep the rules.
Move from Claude to GPT to Gemini andthe policy does not move. The Control Plane, not the model, decides what is allowed and why.
MODEL-AGNOSTIC
Same policy
SAME CHECKS
No uncontrolled data creation
Every write maps to an approved schema
Agents cannot invent fields, createrecords or write outside a defined action. Every change to a system of record is pre-mapped,logged and reversible before it lands.
Schema-bound writes
Pre / post diff
Reversible
Human in the real workflow
Approval inside your real workflow.
The person validating a decision sees thesame case, evidence and rule an analyst would. Approval happens in your existing queue, nota bolted-on review step.
Inline approval
Same queue
Full evidence
NEXT STEPS

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