Selected work / production over promises

Here is what the work looked like in production.

Representative delivery across commercial healthcare, federal civilian, and defense environments—built on real records, connected to real workflows, and judged against an operating result.

90%Touchless processing reached

$80MRevenue tied to an AI product

$35MInitiative supported by contract intelligence

800K+Records connected for federal analysis

01Fortune 10 healthcare

A commercial AI product scaled to 90% touchless processing.

90% touchless$80M product revenue

Challenge: High-volume product records required consistent classification, but fully manual review could not scale with the business.
Approach: A two-tier decision engine applied deterministic rules first, model reasoning second, and routed uncertainty through a multi-persona governance review and feedback loop.
Result: The product line reached 90% touchless processing while preserving a controlled path for exceptions and human review.

02Enterprise healthcare

Contract agents turned restrictive terms into actionable findings.

$35M initiativeTwo-pass verification

Challenge: Critical payment and surcharge language was buried across complex business agreements and difficult to identify consistently with keyword search.
Approach: Extractor and auditor agents processed each agreement in two passes, structured the obligations, and preserved a clause-level citation for every finding.
Result: The workflow supported a $35M operating initiative with findings teams could validate, prioritize, and act on.

03U.S. Department of State

Governed budget knowledge moved from search to decision support.

800K+ recordsHours to seconds

Challenge: Analysts had to navigate hundreds of thousands of records and hundreds of documents to build defensible budget and policy answers.
Approach: A permission-aware assistant planned retrieval, used hybrid search and reranking, generated source-grounded narratives, and retained conversation context.
Result: Research that took hours could be completed in seconds while keeping evidence and permissions attached to the answer.

04U.S. Army

AI agents and operational data met inside Palantir.

AIP + FoundryProduction orchestration

Challenge: Mission workflows needed governed access to multiple data and media sources without creating another disconnected AI interface.
Approach: The delivery connected prompt registries, ontology-backed agents, Azure DevOps data pipelines, retrieval services, and operational Power BI views.
Result: Agents, data, and operational context ran inside the platform the mission already used, creating a reusable foundation for additional workflows.

Representative delivery experience. Outcomes reflect programs led or delivered by OptiSyn leadership and teams; attribution, client ownership, and confidentiality requirements vary by engagement.

WHAT COUNTS AS PROOF

A result a buyer can inspect.

Behavior

A fixed evaluation set shows what the system gets right, where it fails, and how quality changes.

Operation

Cycle time, exception volume, adoption, cost, and human effort stay visible after release.

Trace

Sources, tool calls, decisions, approvals, and system writes remain reviewable.

Ownership

A named team knows who operates, approves, updates, and stops the system.

Start with the workflow

Tell us what is slow, expensive, or stuck.

We will tell you whether an agent belongs in it, what the first production step should be, and where the real risk sits. You will hear back within one business day.

leads@optisynsolutionsllc.com

Business: SDVOSB certified
Delivery: Cleared + regulated
Location: McLean, Virginia

Project briefSecure intake · unclassified