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Data & AI Integration

Legacy-to-AI Bridge Architecture

Bridge architecture for making legacy system data usable by RAG pipelines and AI agents.

Bridge architecture in 3-4 weeks

Engage when

  • Wants AI capabilities (intelligent claims triage, AI-assisted underwriting, "chat with our data" retrieval) but runs on legacy systems
  • has been told "modernize first" but cannot wait 3-5 years
  • RAG or agent pilots failing because legacy data is inaccessible

The engagement

Architecture advisory that designs how enterprises make legacy system data (COBOL, J2EE, monoliths) accessible to RAG pipelines and AI agents without rewriting the core system. Delivers a fixed-fee, implementable Bridge Architecture Blueprint covering API abstraction layers, CDC/event streaming pipelines, vector database integration, and document ingestion strategies. Fills the gap between 'modernize everything first' (3-5 years, millions) and 'bolt AI on top and hope' (fails at scale).

Process

1

Discovery & Legacy Footprint Analysis

Week 1

2

Bridge Architecture Design

Weeks 2-3

3

Roadmap & Handoff

Week 4

Deliverables

  1. Legacy System Inventory & Data Flow Map

    Complete mapping of the legacy estate covering data sources, integration points, current data flows, and the interfaces relevant to AI consumption.

  2. Data Quality Assessment for AI Readiness

    Per-source scorecard covering completeness rate, freshness latency, format parsability, and a RAG-blocking gap list with remediation effort estimates.

  3. API Surface Analysis

    Assessment of which legacy interfaces are exposable via API, which require wrapping, and which need new extraction paths for AI tool-calling.

  4. Bridge Architecture Blueprint

    Technical document covering CDC and event pipelines, API gateway design, vector database integration, RAG chunking strategy, security controls, and monitoring approach.

  5. Implementation Roadmap

    Phased delivery plan with effort estimates, build-versus-buy recommendations, technology choices, risk register, and quick-win identification.

Who This Is For

Typical Buyers

CDO / Head of Data + CTO (jointly)

Industries

Any enterprise with significant legacy estates needing AI data access. Domain depth in insurance (7yr) and banking (5yr)

Part of these journeys

This engagement is a step in these playbooks. See the full plan if you want the longer arc.

Legacy Modernization

A company with a 10-20 year old estate — monoliths, legacy platforms, half-finished migrations — needs AI capabilities, but every initiative stalls on integration complexity. Vendors pitch solutions that assume modern APIs and clean data. Neither exists.

View journey details

AI Modernization Strategy Session

A principal-led analysis of how AI changes the modernization approach for your most critical components.

AI-Powered Legacy Portfolio Scan

AI-driven codebase scan that turns legacy complexity into a modernization-ready map.

or

Legacy-to-AI Bridge Architecture

Bridge architecture for making legacy system data usable by RAG pipelines and AI agents.

Principal Architecture Oversight Retainer

Ongoing architecture governance and decision support for active transformation programs.

Legacy estate mapped, AI opportunities identified, roadmap set.

Related Services

Explore complementary services that build on this engagement.

AI Architecture Diagnostic

A focused, principal-led assessment of your current architecture, AI landscape, and the shortest credible path forward.

3w diagnosticView

Ready to discuss Legacy-to-AI Bridge Architecture?

No commitment. Confidential. A direct conversation to understand your situation and explore how we can help.