Services & Pricing
Plan, Build, and Operate a Customer-Controlled AI Environment.
ConservaTech Networks assesses the operating problem, designs the architecture, deploys private AI infrastructure and governed intelligence, connects organizational knowledge and systems, and supports the resulting environment over time.
Fixed pricing is published for defined planning engagements. Implementation and operations are scoped around the environment, integrations, deployment boundary, and operating requirements.
Start with the appropriate level of investigation.
Free Private AI Readiness Assessment
A self-service fifteen-question profile covering infrastructure, control, knowledge, integration, governance, and operational readiness.
Outcome: An immediate readiness profile and preliminary next-step recommendation.
Take the Readiness Assessment →Free AI Architect Call
A focused 30-minute conversation, with a 60-minute option when additional technical context is needed.
Outcome: An initial fit determination and recommendation for the appropriate paid engagement.
The free assessment produces a preliminary profile. The architect call provides an initial conversation. Neither replaces direct technical investigation or architecture design.
Assess and plan
Choose the depth of planning your decision requires.
Each engagement increases the depth of investigation, architecture, organizational participation, and implementation detail. Select the level that matches the decision your organization needs to make.
Review Foundation Architecture Enterprise Master Plan
Tier 1
Private AI Readiness Review
A human-led expert review of where to begin.
3–5 business days
- Completed Private AI Readiness Assessment
- 90-minute architect working session
- Review of current AI use, systems, boundaries, and objectives
- Identification of the three most important readiness gaps
- Written findings and recommended next step
View complete scope
- Initial private-versus-external workload guidance
- 30-minute findings review
This review does not include detailed infrastructure sizing, system-by-system discovery, security architecture, ontology design, integration design, or a formal target-state architecture.
Led and reviewed by a ConservaTech Networks architect. This is not an automated report.
Best for
Leadership or technical teams that need experienced direction before commissioning formal architecture work.
Tier 2
Private AI Foundation Review
A focused technical review of the required private AI foundation.
1–2 weeks
- Up to two stakeholder interviews
- Initial workload and system inventory
- Preliminary data-boundary review
- Deployment-model analysis
- Initial model-hosting and retrieval recommendations
View complete scope
- High-level infrastructure findings
- High-level integration findings
- Written technical findings
- 60-minute findings review
This is a planning engagement. The In-House AI Foundation is the subsequent implementation service.
Best for
Organizations that need meaningful technical direction before committing to a complete target architecture.
Most common: most commonly selected engagement
Tier 3
Private AI Architecture Assessment
A complete target-state architecture and implementation blueprint.
2–4 weeks
- Current-state systems and data-flow assessment
- AI workload classification and prioritization
- Private model-hosting and retrieval architecture
- Infrastructure and capacity sizing
- Phased implementation blueprint
View complete scope
- Up to six stakeholder interviews
- Private RAG and enterprise-search architecture
- MCP, API, repository, and system-integration plan
- Identity, security, and governance requirements
- Private-cloud and external-provider routing matrix
- Initial cost and capacity model
- Executive findings presentation
This is the blueprint-level engagement.
Best for
Organizations ready to make a private AI infrastructure, architecture, and implementation decision.
Tier 4
Enterprise Intelligence Master Plan
A comprehensive enterprise plan for building, governing, operating, and expanding private AI and governed intelligence.
4–8 weeks
- Cross-functional architecture workshops
- Multi-system and multi-domain architecture
- Enterprise ontology and Knowledge Network strategy
- Implementation waves and dependencies
- Executive decision package
View complete scope
- Detailed deployment topology
- Identity-resolution strategy
- Digital-twin maturity roadmap
- Human-authority and governance model
- Model, agent, tool, and workflow governance
- Security and compliance program requirements
- Capital and operating-cost planning
- Organizational and staffing requirements
- Managed-operations model
The Master Plan incorporates the analysis and work products represented by the preceding assessment levels and extends them into an enterprise-wide architecture, governance, investment, and implementation program.
Best for
Enterprise, regulated, multi-domain, multi-business-unit, or operationally complex organizations.
We will confirm which planning depth fits the decision your organization needs to make.
Build and deploy
Turn the plan into a working environment.
Implementation is scoped around the approved architecture, customer boundary, systems, workloads, security requirements, knowledge model, and operating responsibilities.
In-House AI Foundation
Deploy the customer-controlled infrastructure and runtime required to operate approved private AI workloads.
What it can include
GPU and CPU compute, model serving, storage and networking, identity and secrets, security controls, observability, backup and recovery, approved models, and operational runbooks.
Outcome: A secure customer-controlled AI operating foundation.
Pricing: Scoped engagement — let’s discuss the environment.
Explore Private AI →Private Knowledge and Integration Environment
Connect private knowledge, source systems, retrieval, search, APIs, MCP servers, repositories, and evidence.
What it can include
Private RAG, enterprise search, document ingestion, embeddings, reranking, permissions, source-system mappings, evidence, provenance, retrieval evaluation, and organizational memory.
Outcome: AI grounded in approved organizational knowledge and authoritative systems.
Pricing: Scoped engagement — let’s discuss the environment.
Explore the Knowledge Network →ConservOS Intelligence Deployment
Add governed model routing, workflows, approvals, tools, evidence, audit, cost controls, outcomes, and organizational memory.
What it can include
ConservOS control plane, model and provider policies, agent and tool permissions, workflow state, human authority, evidence requirements, audit history, and outcome capture.
Outcome: A governed operational intelligence environment.
Pricing: Scoped engagement — let’s discuss the environment.
Explore ConservOS →Private Customer Domain
Build a customer-specific governed intelligence environment around proprietary systems, knowledge, workflows, evidence, state, and authority.
What it can include
Customer-specific ontology, identity resolution, current and historical state, computed facts, digital-twin capability, private applications, and approved external context.
Outcome: A customer-controlled intelligence domain built around a specific organization or operational system.
Pricing: Scoped engagement — let’s discuss the environment.
Explore Private Customer Domains →Operate and expand
Choose how the environment will be operated.
Operational scope depends on the deployed infrastructure, model inventory, retrieval pipelines, integrations, availability requirements, security boundary, capacity, and division of responsibility.
Customer operated
The customer’s internal team operates the environment using delivered architecture, runbooks, controls, and support documentation.
Shared operations
Responsibilities are divided between the customer and ConservaTech Networks according to the approved operating model.
ConservaTech Networks managed
ConservaTech Networks monitors and operates the agreed infrastructure, models, retrieval, integrations, security, capacity, backups, lifecycle, and governance boundary.
Managed Private AI Operations
May include infrastructure monitoring, model lifecycle management, retrieval and indexing operations, connector and MCP operations, security maintenance, backup and recovery, capacity management, cost and usage review, provider-policy administration, incident response, governance review, and quarterly architecture review.
Managed-operations pricing is defined around the deployed environment, service levels, support coverage, and division of responsibility.
Discuss Managed Operations →Move from uncertainty to an operating capability.
Assess
Identify the operating problem, workloads, boundaries, systems, risks, costs, and decision requirements.
Architect
Define a target-state infrastructure, knowledge, integration, governance, and operating model.
Deploy
Build and validate the customer-controlled environment.
Connect
Bring authoritative systems, knowledge, evidence, and workflows into the governed operating context.
Govern
Set policies, authority, approvals, routing, audit, and operating measures.
Operate
Observe, support, learn, and improve the environment over time.