Case studies

Challenge. Built. Result.

Real workflows and the numbers behind them. OptiSyn engagements are listed first; the founder’s leadership experience as an employee is labeled separately and is not OptiSyn contract history.

OptiSyn engagements
3
Leadership experience
3
Naming
Only with written approval

OptiSyn engagements

01OptiSyn engagementA specialty construction firm · Construction · Small business

Three disconnected systems became one live P&L in 21 days.

21days to deliver
10+hrs/week of entry eliminated
19governed data views
~$21per month to run
Challenge
Job costs, accounting entries and project spreadsheets lived in three places. Someone re-keyed numbers every week, and the owners saw profit by job only after month-end.
Built
SovereignOS: connectors to three source systems, 19 governed BigQuery views as a single source of truth, and a live P&L and operations dashboard on top.
Result
More than ten hours a week of manual entry eliminated. A live P&L by job. Running cost of roughly $21 a month.
BigQuerySharePointAccounting APIDashboards
02OptiSyn engagementFederal AI program · Subcontract

Budget research moved from hours of searching to cited answers in seconds.

800K+records searchable
Secondsper cited answer, down from hours
Challenge
Analysts had to work across more than 800,000 records and hundreds of documents to build defensible budget and policy answers.
Built
A permission-aware research assistant with SharePoint-native retrieval, hybrid keyword and semantic search with reranking, source-grounded narratives and an audit trail.
Result
Research that took hours returns in seconds, with the citation and the access boundary attached to every answer.
RAGHybrid searchSharePointAudit logging
03OptiSyn engagementFederal AI program · Subcontract

AI agents running inside the platform the mission already uses.

AIP+ Foundry ontology
1platform, no new silo
Challenge
Program teams needed governed AI access to many data and media sources without adding another disconnected AI tool.
Built
Palantir AIP and Foundry agents backed by the ontology, a prompt registry, ontology ETL, Azure DevOps data pipelines and operational Power BI views.
Result
Agents, data and operational context run inside the existing platform, forming a reusable base for the next workflows.
Palantir AIPFoundryAzure DevOpsPower BI
Leadership experience

Healthcare distribution.

Work the founder led as a full-time employee. It shows the architecture and judgment you get; the code and data belong to the employer and are never reused.

01Leadership experienceHealthcare distribution

An item-matching redesign tied to $80M in added revenue.

$80Madded revenue
Challenge
High-volume product records had to be matched consistently, and manual review could not keep pace with the business.
Built
A redesigned matching process that applied deterministic rules first, model reasoning second, and routed uncertain matches to people.
Result
$80M in added revenue attributed to the redesigned process.
Rules + MLHuman reviewEvaluation
02Leadership experienceHealthcare distribution

A contract-eligibility engine that shows its work.

2,089/2,090classified hands-free
37send to end
Challenge
Account eligibility decisions depended on contract terms spread across documents, and every decision needed to be defensible.
Built
A classification engine that evaluated each account against contract rules and recorded the evidence behind every decision, with exceptions routed for review.
Result
2,089 of 2,090 accounts classified hands-free in 37 seconds, each with an evidence trail.
ClassificationEvidence trailsException routing
03Leadership experienceHealthcare distribution

Contract agents that cite the clause behind every finding.

2-passextract + audit
Challenge
Payment and surcharge language was buried in complex agreements and hard to find consistently with keyword search.
Built
Extractor and auditor agents that read each agreement in two passes, structured the obligations and kept a clause-level citation for every finding.
Result
Findings the business could check, prioritize and act on, with a citation a reviewer can open.
Multi-agentCitationsTwo-pass verification

About these summaries. Figures are reported by the client or employer for the work described. They show what was achieved in that context and are not a guarantee of results for another workflow. Client references are available on request where permitted.

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