Explainable AI • Architecture • Governance

Explainable AI systems for regulated enterprises.

We turn fragmented data and documents into traceable decisions — with the architecture, governance, and production controls required for enterprise adoption.

BIS Advisors works with insurance, healthcare/pharma, cybersecurity, risk, audit, and other compliance-driven organizations at every stage of the journey: clarifying the architecture behind an AI concept, validating feasibility as a POC, running a scoped pilot, or preparing a working system for production governance.

Explore the AI Architecture Assessment See what we build

The problems we solve

The POC that stalls

A prototype works in a demo, but the production architecture, data flows, and controls to take it live are unclear — so the initiative stalls, putting the investment at risk.

Results nobody can defend

AI outputs influence decisions, but evidence, provenance, and reasoning are missing — leaving risk, audit, and compliance teams unable to defend or certify the outcomes.

Governance as an afterthought

Security, privacy, and model-risk requirements were never translated into technical architecture — so every step toward production becomes a redesign instead of a checklist.

What we build

Enterprise AI architecture and implementation, with explainability and governance designed in from the start.

Explainable AI & Decision Intelligence

Design scoring, recommendation, and decision-support systems that preserve evidence, provenance, human review, and a clear explanation of how each result was produced.

Learn more →

Enterprise AI & Data Architecture

Define the data flows, identity patterns, integration architecture, governance controls, evaluation practices, and deployment model required to move an AI initiative beyond a disconnected prototype.

Start with an assessment →

AI Document Intelligence

Build grounded systems that retrieve, compare, and interpret complex policies, controls, reports, and evidence while returning traceable answers with source citations.

Read the case study →

Supporting capabilities: hybrid and on-prem LLM deployment, and AI governance designed into the architecture. See the full list on Capabilities.

Ways to engage

Regulated AI Architecture Assessment

A focused architecture and risk review for organizations moving an AI initiative from concept or POC toward production. Fixed scope, approximately 10 business days, prioritized 30/60/90-day roadmap.

POC & Pilot delivery

Scoped proofs of concept and pilots with defined success criteria, representative data, documented limitations, and stakeholder feedback.

Fractional AI & architecture leadership

Ongoing senior architecture and technology leadership — direction, oversight, vendor evaluation, and governance — without a full-time hire.

See how engagements work →

Selected results

Substantiated outcomes from our consulting and delivery work. Each item reflects a separate engagement.

  • Built and validated an AI document intelligence system that, in the evaluated test set, reduced manual lookup time by ~80–90% and returned grounded, cited answers in a few seconds.
  • Designed automated decision systems for approvals that generated $6M+ in incremental profit for the client.
  • Redesigned data flows, integrations, and reporting to cut a monthly financial close cycle from 20 business days to 6.
  • Reduced cloud costs by 30%+ through re-architecture, infrastructure-as-code automation, and workload optimization.

See the AI Document Intelligence case study →

Start with clarity: Regulated AI Architecture Assessment

A focused architecture and risk assessment for organizations moving an AI initiative from concept or POC toward a secure, explainable, production-ready system. You receive a current-state review, a risk register, a target reference architecture, and a prioritized 30/60/90-day roadmap — fixed scope, delivered in approximately 10 business days.

Discuss an AI Architecture Assessment

Supporting consulting partners

Are you a consultancy whose client engagement requires enterprise AI, data architecture, explainability, or governance expertise that is not available internally? BIS provides senior AI architecture capacity — subcontracted, white-label, or client-facing — so you can deliver without making a permanent hire.

Senior AI architecture capacity for consulting partners

About BIS

Business Intelligence Solutions LLC (BIS Advisors) is an enterprise AI architecture and implementation practice helping regulated organizations move AI from concept to governed, production-ready systems. We combine cloud, security, and data engineering expertise with real-world delivery experience in insurance, renewable energy, and enterprise finance.

BIS Advisors is incorporated in Colorado and operates from Florida, serving organizations across the United States. Florida-based clients may request in-person sessions when appropriate.

BIS is led by Dmitry F. — MBA, MS Computer Science, PMP, a principal enterprise architect with 20+ years of delivery across Oracle, Arrow Electronics, RE/MAX, and Carbon Solutions Group — including automated decision systems, large-scale data and integration architecture, and hands-on AI system design and evaluation.

  • AI & LLMs: Retrieval-augmented generation (RAG), grounded Q&A, explainable decision systems, and hybrid/on-prem LLM deployment
  • Cloud & Data: AWS, Azure, GCP • Postgres, Snowflake, streaming pipelines
  • Security & Compliance: SOC 2, ISO 27001, SOX 404, PCI DSS, audit-ready logging and controls

Contact

If your organization is moving an AI initiative toward a secure, explainable, production-ready system — or drowning in long PDFs along the way — we would like to hear about it.

📞 Call us: +1 (303) 632-7874
✉️ Email: consulting@bisadvisors.com

Typical projects

Architecture & assessment → POC or pilot → production planning. Fixed-scope engagements or ongoing fractional leadership.

  • Independent review of an AI POC or vendor design
  • Explainability, provenance, and human-review architecture
  • AI Q&A over SOC 2, NIST, and insurance/cyber documents
  • Hybrid/on-prem LLM deployments on your GPUs or cloud
  • AI governance production-readiness roadmaps