Cloud economics
SpendSmart
Continuous AWS Cost Optimization
Engineering-led FinOps that turns AWS cost data into prioritized savings actions.
- See spend clearly.
- Detect waste early.
- Engineer savings.
20–40%AWS savings potential
OpsTree AI Experience Center
Explore Now →
Forward-Deployed Solutions
The engineering solutions that build your AI factory.
Seven deployable solutions across development, delivery, operations and governance. Deploy one where the constraint is, or connect them across the lifecycle.
Deployable
Connected
Enterprise-grade
AI-enabled
Governed
Outcome-driven
What are Forward-Deployed Solutions?
An AI factory isn’t infrastructure. It’s how your software gets built.
Most AI factory conversations start with compute. The ones that change anything start with the lifecycle.
Forward-Deployed Solutions are the seven pieces that make that work, one per stage, each running on your infrastructure and alongside the tools you already have.
Deploy where the constraint is. Connect them as the factory takes shape.
The Engineering Lifecycle
Seven capabilities. One connected lifecycle.
01 / 07 · CREATE
AI-DLC
AI-assisted software development
Bring AI into requirements, architecture, code, modernization and testing — helping engineering teams move from business context to review-ready changes.
Explore AI-DLC01 CREATE
AI-DLC
AI-assisted software development
Bring AI into requirements, architecture, code, modernization and testing — helping engineering teams move from business context to review-ready changes.
Explore AI-DLCBusiness context
- 01Understand
- 02Specify
- 03Engineer
- 04Validate
- 05Prepare
Review-ready changes
AI applied across
02 · Assure
SentryFuse AI-powered engineering assurance
Evaluate every pull request for change impact, quality, security, maintainability and test adequacy before it moves forward.
SentryFuse works with existing engineering and security tools and provides a readiness assessment before merge.
- Pull Request
- Engineering Signals
- AI Analysis
- Risk Score
- Review / Action
Pull request · before merge
Readiness assessed
Illustrative view of a readiness assessment.
Deliver
BuildPiperEnterprise software delivery and DevSecOps
Standardize software delivery across Kubernetes, VMs, Windows, mobile applications and cloud environments with automation, security, compliance and full-stack visibility.
- 5×faster time to market
- 40–60%reduction in tooling spend
- 10 hrsper week saved per developer
- 99.9%reliability and compliance at scale
- Code
- Build
- Test
- Secure
- Deploy
- Operate
Delivers across
- Kubernetes
- VMs
- Windows
- Mobile applications
- Cloud environments
REMS + Olly
Operate
Operate
REMS + Olly
AI-powered observability and SRE
Unify metrics, logs, traces and SLOs across the technology stack. Apply AI to diagnose root causes, recommend remediation and coordinate incident response.
- Unified observability
- AI-assisted diagnosis
- SLOs and error budgets
- Structured incident response
- AI-assisted RCA
The solution is built on open-source and cloud-native foundations.
Govern
AI Gateway
Enterprise AI governance and model operations
Create a governed path to every model through centralized access, model routing, token optimization, security policies, cost controls and usage visibility.
One API. One policy layer. One governed path to AI.
Enterprise demand
AI Gateway
One API · One policy layer
- Centralized access
- Model routing
- Token optimization
- Security policies
- Cost controls
- Usage visibility
Model ecosystems
- Scoped access
- Automatic failover
- Self-hosted control
Business layer
AI-powered signal correlation
Technology signals
Observe
Business Observability
Connect business outcomes to technology signals.
Bring real-time visibility to business KPIs and customer journeys while connecting changes in business performance to the technology signals behind them.
- Business KPIs
- Customer journey visibility
- Predictive intelligence
- AI-powered signal correlation
- 40%faster insight access
- 30%faster root-cause analysis
- Secure localAI deployment
Optimize
Optimize the infrastructure behind transformation.
Optimization extends across cloud economics, Kubernetes operations and infrastructure security.
Kubernetes operations
KubeLift
EKS upgrades from weeks to hours.
AI-assisted automation across the complete EKS upgrade lifecycle — from pre-flight risk checks through execution, reconciliation and validation.
50+production EKS clusters upgraded
Zerodowntime incidents
Infrastructure security
Security Patching
Compliance without service disruption.
A controlled patching program across applications, middleware, databases, operating systems and cloud-native infrastructure.
- Risk-prioritized planning.
- Phased patching.
- Availability protection.
- Post-patch validation.
- Audit-ready evidence.
The FDS Model
Deploy where the constraint exists.
01 / 05
Enterprise transformation doesn't need to happen all at once.
Start with the engineering challenge that matters.-
01
Discover
Understand the environment, constraint and desired outcome.
-
02
Deploy
Introduce the right Forward-Deployed Solution into the environment.
-
03
Adopt
Integrate the capability into existing engineering workflows and teams.
-
04
Connect
Extend the solution across adjacent capabilities where transformation requires it.
-
05
Scale
Expand what works across applications, teams and environments.
DISCOVER
→
DEPLOY
→
ADOPT
→
CONNECT
→
SCALE
AI Across the Engineering Lifecycle
AI creates speed. Engineering creates control.
AI is changing how software is created, reviewed, delivered and operated.
The Requirement
01
New requirements arrive with AI.
But enterprise AI adoption also introduces new requirements around:
The Response
02
Controls across the lifecycle.
OpsTree Forward-Deployed Solutions bring AI into the engineering lifecycle with controls around how AI is created, assured, delivered, governed, observed and optimized.
Engineering control
01
AI-assisted software development
02
AI-powered engineering assurance
03
AI governance
04
AI observability
05
Intelligent operations
AI Across the Engineering Lifecycle
AI creates speed. Engineering creates control.
AI is changing how software is created, reviewed, delivered and operated.
01
The requirement
New requirements arrive with AI.
But enterprise AI adoption also introduces new requirements around:
Engineering requirements
Quality
Security
Governance
Cost
Reliability
Observability
The shift
- AI adoption
- New engineering requirements
- Engineering control
02
The response
Controls across the lifecycle.
OpsTree Forward-Deployed Solutions bring AI into the engineering lifecycle with controls around how AI is created, assured, delivered, governed, observed and optimized.
AI engineering lifecycle
01
AI-assisted software development
02
AI-powered engineering assurance
03
AI governance
04
AI observability
05
Intelligent operations
Controlled engineering path
- Create
- Assure
- Deliver
- Govern
- Observe & optimize
03
Engineering outcomes
Control turns AI into an engineering system.
Measurable impact
50%+
fewer non-actionable alerts
~25%
less investigation time
~20%
lower CI/CD maintenance
AI + engineering control
Speed with governance, assurance and operational visibility.
One Connected Engineering Lifecycle
Solutions that work better together.
Forward-Deployed Solutions can solve an individual engineering constraint. But transformation often crosses multiple layers.
01 / 07
Create
Business Outcomes
RESULT
Applications
→
Data
→
AI
→
Platform
→
Cloud
→
Delivery
→
Operations
Forward-Deployed Solutions + Co-Engineering
Engineering expertise meets deployable solutions.
Forward-Deployed Solutions provide the engineering capability. Forward-Deployed Engineering brings OpsTree expertise directly into the enterprise environment.
01
Engineering expertise
+
02
Deployable solutions
+
03
Enterprise context
CO-ENGINEERING
Engineering expertise meets deployable solutions.
Together, they bring engineering capability directly into the enterprise environment.
Together, they help enterprises move from
Challenge
→
Outcome
Engineering expertise, deployable solutions and enterprise context work together across the transformation journey.
- 01 Challenge
- 02 Deployment
- 03 Adoption
- 04 Scale
- 05 Outcome
Engineering expertise meets deployable solutions.
Explore Co-Engineering08 / Frequently asked questions
Frequently asked questions.
01 / 07
What are Forward-Deployed Solutions?
Forward-Deployed Solutions are deployable engineering capabilities designed to address enterprise technology challenges across software development, engineering assurance, software delivery, production operations, AI governance, business observability and infrastructure optimization.
02 / 07
What Forward-Deployed Solutions does OpsTree offer?
OpsTree's FDS portfolio includes AI-DLC, SentryFuse, BuildPiper, Olly + REMS, AI Gateway, Business Observability, SpendSmart, KubeLift and Security Patching.
03 / 07
Are Forward-Deployed Solutions only for AI?
No. AI is an important layer across the portfolio, but FDS spans the broader software and technology lifecycle — including software development, DevSecOps, observability, SRE, AI governance, business observability and infrastructure optimization.
04 / 07
Can Forward-Deployed Solutions be deployed independently?
Yes. Each capability can be deployed independently or combined with other capabilities across the engineering lifecycle.
05 / 07
How are FDS different from traditional consulting?
FDS are designed as deployable engineering capabilities that can work inside existing enterprise environments, engineering workflows and technology stacks.
06 / 07
How does FDS support enterprise AI adoption?
FDS applies AI across software development, engineering assurance, delivery, operations, governance, business observability and infrastructure optimization — helping enterprises move from experimentation toward governed and measurable AI engineering.
07 / 07
What enterprise environments can FDS support?
The portfolio is designed around complex enterprise environments spanning cloud, hybrid, on-premises, Kubernetes, enterprise applications, CI/CD systems and infrastructure. The individual solution capabilities vary by use case.