The Approach

A 6-week delivery model. Not a 6-month pilot.

How we connect, read, build and ship: week by week, with a human-AI split agreed before work starts.
DELIVERY MODEL

Week by week, from access to production.

The context, rules and judgment of your best engineer live in the platform, not in one person's head. That's what lets every developer on your team perform like them. Click each step.
DAY 1-2 / access established
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CONNECT
We connect to what you already run. Nothing changes.
Forward-Deployed Engineers, on-site or remote, connect to your repositories, project tools, databases, logs and documentation. CISO sign-off on an architecture diagram is a prerequisite for this stage.
code
GITHUB
GITHUB
GITlab
GITlab
JIRA
bitbucket
CONFLUENCE
AZURE DEVOPS
work
JIRA
JIRA
SERIVCENOW
SERVICENOW
docs
CONFLUENCE
CONFLUENCE
CONFLUENCE
sharepoint
NOTION
NOTION
data
NOTION
oracle pi
DATADOG
sql server
DATABASE
postgre sql
CONFLUENCE
imb db2
OPS
DATADOG
DATADOG
SPLUNK
SPLUNK
CONFLUENCE
dynatrace
SPLUNK
CISO REVIEW
No rip-and-replace. No new toolchain. We adapt to what you already run.
WEEK 1 / SANDBOX LIVE
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Deploy Sandbox
GalentAI sandbox deploys inside your cloud, configured for your compliance perimeter.
Deployed inside AWS, Azure, GCP, on-prem, or air-gapped. SSO, tenant isolation, RBAC/ABAC. Connects to your approved LLM providers. Every developer now works inside the same governed sandbox as your most experienced engineer. Your SSO, your approved models, your network boundary
KUBERNETES
aws
KUBERNETES
azurE
KUBERNETES
GCP
KUBERNETES
OKTA
KUBERNETES
ENTRA(SSO)
KUBERNETES
hashicorp
KUBERNETES
aws bedrock
KUBERNETES
KUBERNETES
HELM
HELM
TENANT ISOLATION
TENANT ISOLATION
RBAC
RBAC
ABAC
ABAC
CDKTF MULTICLOUD
CDKTF MULTICLOUD
AI chatbotAI chatbotAI chatbot
By week 1: sandbox live in your cloud, SSO connected, first agents running.
WEEK 2-3 / yOUR SYSTEMS, READ
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BUILD GRAPHS
We read your systems before we write a line.
GalentAI reads source code, schemas, APIs, tickets, runbooks and logs into theKnowledge Graph: what exists and how it connects. The Context Graph encodes yourarchitecture principles, compliance rules and standards as enforceable policy. By the end ofweek 3, every agent and engineer works from the same map.
MONGODB ATLAS
repos(ast)
MONGODB ATLAS
DB
SCHEMAS
MONGODB ATLAS
api
MONGODB ATLAS
ITSM
TICKETS
MONGODB ATLAS
RUNBOOKS
MONGODB ATLAS
LOGS
MONGODB ATLAS
ADR
MONGODB ATLAS
MAINFRAME
(COBOL/JCL)
AST parsing (Neo4j)
neo4j
MONGODB ATLAS
MONGODB ATLAS
ADR ENCODING
postgre sql
Redis
(45ms P95)
Redis
(45ms P95)
By week 3: dependency map, hot-path report and a ranked list of possibilities.
WEEK 3-4 / SPEC VERIFIED BEFORE CODE
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FIRST EPIC
No code without a verified plan. Every task classified across four human-AI modes.
The Spec Agent generates features, epics, stories, acceptance criteria, and NFRs, pushed to Jira before any code generation. Each task is classified, and the human-to-AI ratio is agreed, embedded in the plan, and enforced.
SPEC AGENT
SPEC AGENT
SPEC AGENT
JIRA
SPEC AGENT
SPEC AGENT
SPEC AGENT
LINEAR
JIRA PUSH
JIRA PUSH
4 MODE ENGINE
4-MODE ENGINE
HITL GATE
HITL GATE
DATALOG
DECISION LOG
By week 4: first epic specified, every task classified, human-AI split signed off.
WEEK 5-6 / FIRST RELEASE, FULLY TRACED
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VALIDATE
The first epic ships. Every decision behind it is on record
Code is validated at every stage: tests generated with the code, security anddependency scans, architecture checks through the RCM Engine and human gates at epiclevel. It releases through your CI/CD, and results are measured against the week-1 baseline.
list
TEST AGENT
code
critic agent
list
validation agent
RCM
sonarqube
search
snyk
RCM
RCM ENGINE
search
TRACEABILITY MATRIX
warning
RED-TEAM HARNESS
RCM
github actions
search
argocd
Explainability is built into every sprint. Your board can inspect any decision at any time.
green circle
WEEK 6+ / PLATFORM COMPOUNDS OVER TIME
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SCALE
Every sprint starts from more than the last one.
The Knowledge Graph updates with every commit and the Context Graph with everyarchitectural decision. New agents join the library as patterns repeat. You own the software,the graphs, the agents built for you and the full audit trail.
reset
CONTINUOUS
GRAPH UPDATES
smart
AGENT
EVALS
branch
PROMPT
VERSIONING
robot
175+ AGENT
LIBRARY
robot
EXECUTIVE
DASHBOARD.
From week 6: reuse rate, cycle time and defect trends visible on the Executive Dashboard.
HUMAN-AI COLLABORATION

Four modes. 

Every task classified before work starts.

Regulators and Compliance ask who decided. Every task in the plan is classified beforework starts, the human-to-AI split is agreed with you, and the platform enforces it. Even the fully human decisions are recorded.
01/full ai
02/ai + validation
03/hUMAN LEADS
04/FULLY HUMAN

AI executes. Context checks.

Well specified work where the Context Graph already holds the answer: your standards, your patterns, your schemas. The Critic agent reviews every output; people sample ratherthan sign off.

90%
AI : HUMAN RATIO
10%
Coding standards, API contracts, schema map· Critic agent plus sampled human review
TEST CASE CREATION FROM ACCEPTANCECRITERIA
UNIT TEST GENERATION
tEST DATAGENERATION
CODE GENFOR SPECIFIED MODULES
CODE GENFOR SPECIFIED MODULES
API DOCUMENTATION
CONFIG & IAC TEMPLATES
DEPENDENCY UPGRADES
LOG TRIAGE & TICKET CLASSIFICATION

AI builds. An engineer approves.

AI drafts from the graph, theplatform checks it against Context Graph rules, and an engineer approves before anything merges.

70%
AI : HUMAN RATIO
30%
Business rules, data lineage, integration contracts · Named engineer at merge
BUSINESS LOGIC
MIGRATION SCRIPTS
SCHEMA CHANGES
COMPLEX INTEGRATIONS
LEGACY MODULE
REFACTORING
REGRESSION SUITES
PERFORMANCE TEST SCRIPTS
DATA MAPPING & TRANSFORMATION
ROOTCAUSE DRAFTS (RCM)

An engineer designs.
AI checks it against your context.

Senior engineers make the call; AI tests it against the graph: every dependency it touches, every rule it could break, every downstream system. The same rules apply to human work as to AI work.

40%
AI : HUMAN RATIO
60%
Dependency graph, architecture principles, security policy · Architect or tech lead
ARCHITECTURE DECISIONS(ADRS)
IMPACT ANALYSIS
THREAT MODELING
SECURITY POLICY
API CONTRACT DESIGN
NOVEL SYSTEM DESIGN
HIGH-RISK MIGRATIONS
CUTOVER PLANNING

People decide.
The platform remembers.

Judgment, accountability and relationship sstay with people. GalentAI supplies the context and records the decision, so the reason outlives the person who made it.

0%
AI : HUMAN RATIO
100%
Full graph for context, decision log for therecord · Business owner, CISO or chang eboard
Stakeholder alignment
Ambiguity resolution
Exception approvals
Production authorizations
GO / NO-GO CALLS
RISK ACCEPTANCE
REGULATORY SIGN-OFF
THE PLATFORM BEHIND IT

See what makes six weeks possible.

view the platformPLAN YOUR SIX WEEKS
Galent pairs Forward-Deployed Engineers with GalentAI to read, modernize, build and run enterprise software, with your context staying in your cloud.
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