- What this is
- Microsoft-native governed AI reference architecture. Hybrid query engine routing business questions to SQL for precision, RAG for semantic search, or both — every response cited to a specific source row or document.
- Who it’s for
- Regulated buyers — federal civilian, regulated commercial, and enterprise teams whose AI outputs must trace to a source of record under FAR, DFARS, or audit obligations.
- Reference architecture
- Azure OpenAI · M365 + SharePoint/OneDrive · Azure Data Services · Copilot Studio + Power Automate. Also delivered on AWS-native, Anthropic-native, or hybrid stacks.
- Engagement model
- Three-phase delivery — foundation → expansion → advanced intelligence. Workstream-lead accountability within the prime’s implementation team.
Capability Detail
Hybrid Data Intelligence Platform
Governed AI for regulated buyers. A hybrid query engine that routes business questions to SQL for precise calculations, to Retrieval-Augmented Generation (RAG) for semantic search across documents, or to both for combined answers — every response cited to a specific source row or document.
Founder past performance — detailed personnel credentials available under NDA. See Past Performance.
Overview
Why hybrid routing
Single-mode retrieval breaks in regulated environments. Pure SQL cannot answer questions that require document context. Pure RAG cannot answer questions that require precise numeric calculation. Both modes alone produce answers that fail audit when the question crosses both surfaces.
The Hybrid Data Intelligence Platform routes each question to the surface that can answer it correctly — SQL for precision, RAG for semantic search, or both for combined answers — and binds every response to a specific source row or document. The result is an AI delivery posture compatible with FAR, DFARS, and federal compliance frameworks where every claim must trace to a source of record.
Reference Architecture
Microsoft-native delivery posture
The reference architecture deploys on Azure OpenAI for model inference, Microsoft 365 and SharePoint/OneDrive for document grounding, Azure Data Services for structured query, and Copilot Studio with Power Automate for agent orchestration. This stack aligns with existing federal and enterprise Microsoft tenancy commitments, simplifies identity and access control under Entra ID, and inherits Microsoft's regulated-tenant compliance posture (Azure Government, GCC, GCC High where required).
Hybrid Data Intelligence Platform is also delivered on AWS-native, Anthropic-native, or hybrid stacks when client environment, sovereignty requirements, or workload economics dictate. Architecture pattern remains the same; the substrate changes.
Delivery Model
Three-phase implementation
Foundation
Identity, access, and tenant baseline. Source-of-record mapping for both SQL and document surfaces. Initial routing rules. Audit logging and observability scaffolding. Reference dataset and pilot query set scoped with the buyer.
Expansion
Production query surfaces extended across additional source systems. Routing rules tuned against real query traffic. Citation rendering hardened for downstream consumers (analyst review, audit response, executive briefings). Role-based response gating.
Advanced Intelligence
Agentic workflows in Copilot Studio. Multi-step reasoning with controlled tool use. Scheduled summaries and exception reporting. Integration with downstream business systems via Power Automate. Continuous evaluation against accuracy and citation-completeness scorecards.
Use Cases
Where hybrid routing earns its keep
Use cases share a common shape: the buyer must answer a question that requires both quantitative precision and document context, the answer must trace to a source of record, and the workflow cannot tolerate hallucinated or unsourced output.
- Compliance evidence retrieval. Audit response queries that require both control-implementation narrative (RAG) and control coverage metrics (SQL), with citation to the controlling policy document and the source telemetry row.
- Past-performance synthesis. Contract opportunity screening that pulls relevant past-performance narrative from contract files (RAG) and matches it against scoped work category, dollar value, and period-of-performance data (SQL).
- Operational reporting. Executive question-answering across structured operational metrics and unstructured incident reports, with both numeric values and supporting narrative cited inline.
- Regulated knowledge management. Field-team and analyst question-answering across SharePoint, OneDrive, and line-of- business systems, with role-based response gating and source attribution on every answer.
Capability Summary
What the platform delivers
- Hybrid query routing — SQL precision plus RAG breadth
- Source-cited answers, audit-ready from day one
- Microsoft-native reference architecture (Azure OpenAI · M365 · Copilot Studio · Power Automate)
- Alternate substrates available — AWS-native, Anthropic-native, hybrid
- Three-phase delivery — foundation, expansion, advanced intelligence
- Role-based response gating and access control under Entra ID
- Compatible with Azure Government, GCC, GCC High regulated tenancy
- Senior workstream leadership; documentation-first delivery posture
Common Procurement Questions
What buyers ask about the Hybrid Data Intelligence Platform
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Does the Hybrid Data Intelligence Platform require Azure Government, GCC, or GCC High tenancy?
No. The Hybrid Data Intelligence Platform deploys on the buyer's existing Microsoft tenancy regardless of regulated-tenant classification. For federal civilian agencies and Defense Industrial Base buyers handling Controlled Unclassified Information (CUI), deployment proceeds inside the buyer's Azure Government, Government Community Cloud (GCC), or GCC High tenant per the data classification scope of the engagement. For commercial buyers, deployment proceeds inside the buyer's Azure Commercial tenant.
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Can outputs be audited under Federal Acquisition Regulation (FAR) Part 39 and DFARS 252.204-7012?
Yes. The platform is designed around the source-citation requirement that audit-bound workloads carry. Every response binds to a specific source row (for Structured Query Language results) or a specific document and page or section (for Retrieval-Augmented Generation results), with the underlying retrieval pipeline emitting traceable audit log entries that can be exported to the buyer's evidence collection system. The architecture is compatible with FAR Part 39 acquisition oversight and DFARS 252.204-7012 cyber incident reporting obligations when deployed inside the buyer's compliant tenant.
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What is the minimum pilot scope?
A typical Phase 1 (Foundation) pilot is scoped to one source-of-record system, one document corpus, and one buyer-defined query set covering between 25 and 75 representative questions. Pilot delivery time is six to ten weeks depending on tenant readiness, identity and access baseline status, and source-system access cadence. Pilots produce tenant-resident artifacts that are reusable in subsequent phases — never throwaway scaffolding.
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Does CSG hold independent third-party certification under CMMC, FedRAMP, or ISO 27001?
No. CSG does not currently hold independent third-party certification under the Cybersecurity Maturity Model Certification, the Federal Risk and Authorization Management Program, ISO 27001, or equivalent frameworks. The Hybrid Data Intelligence Platform operates within the buyer's certified or authorized environment. Where a solicitation requires firm-level certification, CSG surfaces this posture explicitly in the response framing. See Government Acquisition for SAM and certification pathway status.
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Can the platform be delivered on AWS GovCloud or Anthropic Claude for Enterprise instead of the Microsoft stack?
Yes. The Hybrid Data Intelligence Platform pattern is substrate-agnostic. AWS-native delivery uses Amazon Bedrock for inference, Amazon OpenSearch or Kendra for retrieval, and AWS Step Functions for orchestration. Anthropic-native delivery uses Claude for Enterprise or Claude Code with retrieval grounded against the buyer's document corpus and structured systems. Hybrid combinations (Anthropic inference on Microsoft retrieval, for example) are supported when buyer environment, sovereignty requirements, or workload economics dictate. Architecture pattern remains constant across substrates.
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How does the platform avoid hallucinated or unsourced output?
The platform constrains the response surface to outputs the retrieval layer can ground. Queries that route to Structured Query Language return numeric values from named source tables with row-level attribution; queries that route to Retrieval-Augmented Generation return text spans with document and section citations. Questions the platform cannot ground return an explicit "insufficient source coverage" response with a routing diagnostic, not a fabricated answer. Citation completeness and accuracy are tracked against a published scorecard methodology refined per engagement.
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How is past performance attributed when the engagement was performed at a prior employer or prime?
CSG presents past performance under the federal eight-element narrative attribution framing. Founder past performance is sourced from prior employer and prime engagements and made available under Mutual Non-Disclosure Agreement to qualified prospects in capture-volume and proposal-volume formats. See Past Performance for the engagement slate. See Leadership for the personnel disclosure package available under MNDA.
Request a capability brief
Discussing a regulated AI delivery requirement, evaluating a hybrid retrieval architecture, or scoping a pilot? Send a capability inquiry and we will respond within one business day.
Reviewing procurement fit? See Government Acquisition for North American Industry Classification System (NAICS) coverage, SAM registration status, and contract-vehicle pursuit posture.