Representative engagements

Problems we actually solve

Drawn from active and prior program experience across federal civilian, defense, healthcare, telecom, and commercial environments. These are the shapes of problem Fortis is built for.

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Public Trust  ·  Federal Civilian
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Representative engineering experience drawn from programs led by Fortis leadership in prior and current roles. Program identities, sensitive architectures, and client details are withheld. These examples demonstrate relevant experience and are not represented as Fortis corporate contracts.
Federal · Regulated estate · Multi-cloud

Consolidating a sprawling database estate onto a governed multi-cloud platform

Challenge

A large regulated organization needed to move several hundred databases across five engines onto governed cloud platforms, inside an accreditation boundary, with near-zero downtime tolerance and fixed delivery windows that could not slip. The estate had grown without a provisioning standard, so no two environments were configured the same way.

Engineering approach

Fortis leadership owned the database engineering workstream: assessment of the existing estate, a target architecture per platform, infrastructure as code standards so every environment provisioned to the same compliant baseline, right-sizing analysis, and phased migration with validation gates at every stage.

Outcomes
Several hundred databases migrated across multiple cloud platforms with no data loss
Provisioning standardized as code, so compliance posture became repeatable rather than reviewed
Material cost reduction delivered through right-sizing and consolidation
Backup, replication and failover standardized through automated runbooks across tenants
Multi-cloudGovernment cloudTerraformAnsibleAccreditation boundaryOraclePostgreSQLSQL Server
Defense · Edge and disconnected systems · Distributed architecture

Replication that holds integrity through extended loss of connectivity

Challenge

A defense program needed replication that keeps data consistent on edge systems operating under intermittent and unreliable connectivity. Managed cloud databases cannot run in a disconnected environment at all, and the legacy occasionally-connected sync layer had reached the limit of what it could be maintained through.

Engineering approach

Fortis leadership designed a hybrid architecture running self-managed databases at the disconnected edge, syncing with managed databases at the core, then drove the transition from occasionally-connected replication to event-driven replication: a durable queue-and-replay design that holds integrity across an outage of any duration.

Outcomes
Edge database architecture designed to sync reliably with managed databases at the core
Event-driven replication architected to replace an ageing occasionally-connected sync layer
Durable queue-and-replay design holding integrity through extended loss of connectivity
Architecture documentation produced and adopted as the reference across the program
Event streamingDisconnected syncSelf-managed at the edgeManaged at the coreDoD RMF
Commercial · Healthcare and eCommerce · Performance

Performance optimization and a 30 percent reduction in unplanned downtime

30%
Reduction in unplanned downtime
25 to 30%
Query performance improvement on critical workloads
15+ hrs
Manual operational work automated each week
Challenge

A healthcare and eCommerce organization was experiencing recurring unplanned downtime, performance bottlenecks on customer-facing systems, and audit readiness gaps across SQL Server, PostgreSQL, MySQL, and cloud-hosted environments supporting more than a thousand business users.

Engineering approach

Implemented a proactive monitoring architecture, performed deep analysis on the critical query workloads, redesigned indexing on high-traffic tables, and automated the recurring operational tasks that were consuming engineer hours every week.

Outcomes
Reduced unplanned downtime by 30 percent while holding uptime commitments
Delivered 25 to 30 percent query performance improvement on critical workloads
Automated more than 15 hours per week of manual operational work
Reached full audit readiness across production database environments
SQL ServerPostgreSQLMySQLCloudWatchSplunkNew RelicPowerShellSOX
Commercial · ETL and integration · BI platform

Multi-terabyte pipeline engineering for a thousand-user analytics platform

1,000+
Daily users on the reporting platform
Multi-TB
Datasets processed across heterogeneous systems
Challenge

The organization needed reliable pipeline architecture processing several terabytes daily across Oracle ERP, SQL Server, MySQL, and Redshift, supporting analytics for over a thousand business users under strict latency and data quality requirements.

Engineering approach

Designed and implemented end-to-end pipeline architecture, integrated data across the ERP and operational systems, and supported the warehouse and reporting layer with alerting, monitoring, and automated error recovery.

Outcomes
Engineered pipelines processing multi-terabyte datasets across heterogeneous systems
Supported warehouse and reporting environments serving a thousand-plus users daily
Held uptime commitments across all production data pipelines
Unified ERP, relational, and cloud sources into a single data platform
SSISInformatica IICSQlik ReplicateOracle ERPRedshiftTableauSSAS
Commercial · Telecom · HA and DR

Enterprise telecom high availability and operational automation

25 to 30%
Performance improvement on key application databases
15+ hrs
Manual database operations automated each week
Challenge

A telecom provider needed high availability and disaster recovery architecture across SQL Server, Oracle, and MySQL environments supporting both commercial and government workloads, while cutting the manual effort consumed by daily database operations.

Engineering approach

Implemented availability groups, clustering, and log shipping. Ran performance analysis to isolate CPU, disk, and memory bottlenecks. Built an automation library covering monitoring, maintenance, alerting, and routine operations, and integrated managed cloud databases for the hybrid layer.

Outcomes
Achieved 25 to 30 percent performance improvement on key application databases
Implemented HA and DR supporting production uptime commitments
Automated more than 15 hours per week of manual database operations
Integrated managed cloud databases with on-premise systems for hybrid architecture
SQL ServerOracleMySQLAlways On AGClusteringPowerShellAWS RDSAurora
Commercial · Healthcare · Clinical systems

Clinical database platform administration and recovery strategy

Challenge

A healthcare organization required documented, reliable database administration for clinical and operational systems, with a comprehensive disaster recovery strategy, performance optimization, and pipelines supporting clinical reporting workflows.

Engineering approach

Took full lifecycle ownership across production, test, and development. Designed a recovery strategy with full, differential, and log backup chains and regularly tested restore procedures. Built the clinical reporting pipelines and tuned the workloads behind them.

Outcomes
Designed and validated a recovery strategy with tested recovery objectives
Optimized clinical system performance through query tuning and index redesign
Built the pipelines supporting clinical and operational reporting
Maintained around-the-clock production support for clinical systems
SQL ServerSSISBackup and restoreQuery tuningClinical systemsHIPAA
AWS · GenAI · Reference build

Full GenAI data assistant: retrieval, document intelligence, and delivery pipeline

~30x
Faster reads through the cache-aside layer
~90 sec
Commit to running instance, automated
Challenge

Design and build a production-grade generative AI data assistant end to end, combining model integration, voice control, document intelligence, analytics, and automated delivery into one coherent architecture, using the same patterns as active federal cloud and data programs.

Engineering approach

Built three interfaces over a shared backend, integrated OCR for document pipelines and image analysis with confidence scoring, stood up a knowledge base for retrieval, added a cache-aside layer for latency, and wired a full pipeline that deploys to compute automatically on push.

Outcomes
Retrieval pipeline grounding model responses in private data rather than invention
OCR pipeline converting physical documents into structured relational records
Cache-aside layer delivering roughly thirty times faster reads than the database path
Key design rebuilt around record identity to make writes idempotent
Automated delivery from commit to running instance in about ninety seconds
Architecture fully documented and handed over as part of delivery
Amazon BedrockClaude APIAWS LambdaTextractRekognitionSageMakerRDS PostgreSQLDynamoDBElastiCacheCodePipelinePython and boto3

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