Services

Service lines for AI strategy, architecture, and execution

NewCo360 is structured as a services business first. Proven modules exist to accelerate delivery, but the commercial offer is built around diagnosing, designing, implementing, and optimizing AI systems.

AI strategy & architecture

Strategic and technical definition of where AI should be applied, how the architecture should evolve, and what should remain private, hybrid, or provider-managed.

Roadmap for AI initiatives tied to business and operating constraints
Architecture review covering data flows, deployment paths, and vendor exposure
Practical build plan for MVP, pilot, or production modernization

Supporting building blocks

Architecture review patterns Private AI references Platform decision framework

Private AI, RAG & knowledge systems

Design and implementation of internal copilots, retrieval systems, AI knowledge workflows, and secure data-aware experiences for enterprise contexts.

Private AI chat experiences backed by controlled data access
RAG pipelines with multimodal ingestion and production-grade retrieval
Persistent memory and structured context for agent and assistant systems

Supporting building blocks

Private AI deployment blueprint Retrieval and ingestion framework Persistent memory layer Secure conversational interface patterns

Performance & cost engineering for AI workloads

Profiling and redesign of AI workloads, cache layers, serving topology, and data paths to improve latency, resilience, and infrastructure economics.

Latency and throughput diagnostics with measurable remediation plan
Model-serving cost/performance tradeoff analysis
Optimization of analytics, NLP-to-SQL, and retrieval-heavy systems

Supporting building blocks

Conversational analytics architecture Benchmarking methodology Usage and observability data layer Distributed inference blueprint

Implementation & product engineering

Hands-on delivery for AI-native products, admin surfaces, orchestration layers, and internal tools that need to move from concept to operational software.

Solution design and implementation with engineering ownership
Admin surfaces, SDKs, billing, auth, and operational tooling
Bots, workflows, and integrations connected to the rest of the stack

Supporting building blocks

Workflow builder patterns Agent orchestration layer Operational console foundation Integration and automation connectors

Engagement models

AI diagnostic

Short engagement to assess opportunities, risks, and technical constraints before a larger commitment.

Best when leadership needs a clear starting point, architecture direction, and prioritization.

Architecture review

Deep technical review of a current system, initiative, or vendor setup with a remediation and modernization plan.

Best when a team already has something running, but performance, cost, or platform decisions are unclear.

Implementation sprint

Focused delivery for a defined scope such as RAG, private AI, orchestration, analytics, or infra optimization.

Best when the problem is known and the business needs execution, not another discovery deck.

Embedded engineering partner

Ongoing architecture and engineering support alongside internal product, data, and platform teams.

Best when a company needs continuity from roadmap through production operation.

Private AI foundation

Reusable architecture for sovereign AI chat, internal copilots, provider routing, and controlled access boundaries.

Retrieval and knowledge framework

Document ingestion, retrieval, chunking, and knowledge orchestration patterns for enterprise AI workflows.

Conversational analytics stack

Building blocks for NLP-to-SQL, semantic caching, entity resolution, and conversational access to data.

Distributed inference architecture

Serving patterns for hybrid and private AI workloads where cost, latency, and hardware utilization matter.

Workflow and agent orchestration layer

Coordination layer for tools, workflows, agent collaboration, and operational control surfaces.

Persistent memory services

Context and memory services for AI assistants and agents that need continuity, recall, and session isolation.