Data is the core. Fortis delivers data platform and database engineering first, supported by the cloud infrastructure, modernization, SRE and DevSecOps, analytics and AI disciplines required to make modern data platforms reliable, secure, scalable and useful. One lifecycle runs through all of it: Design → Build → Modernize → Automate → Operate.
Request an assessmentThe foundation and organizing capability. Database and data-platform depth across major platforms, delivering the reliability, performance, movement, governance and compliance posture that production programs depend on.
Full lifecycle DBA work across SQL Server, PostgreSQL, Oracle, MySQL, MariaDB, and MongoDB. Installation, configuration, patching, upgrades, capacity planning, and operational support for systems that cannot go dark.
Engage this serviceDeep analysis using execution plans, wait statistics, and I/O profiling. Query optimization, index redesign, and instance tuning aimed at root causes rather than symptom management.
Engage this serviceAvailability groups, transactional and merge replication, log shipping, and Kafka event-driven architecture, including systems that operate under intermittent or denied network connectivity.
Engage this serviceClustering, failover automation, backup chain design, and recovery procedures that have actually been tested. Built to hold uptime commitments and continuity of operations requirements.
Engage this serviceDatabase architecture aligned to FedRAMP, FISMA, DoD RMF, and SOX. Role-based access control, encryption at rest, and audit logging designed in from the first commit.
Engage this serviceRoot cause analysis for deadlocks, blocking chains, replication failures, corruption, and performance emergencies on production systems, with remediation and post-incident documentation.
Engage this serviceThe infrastructure around the data platform: compute, networking, storage, identity and Kubernetes, built as code across AWS and AWS GovCloud, Azure and Azure Government, Google Cloud and Oracle Cloud, with the strongest production depth in AWS.
Account and network structure, identity boundaries, compute and storage sizing, and the security controls a program has to evidence at authorization. Designed around the workload and the compliance boundary rather than copied from a reference diagram.
Engage this serviceTerraform and Ansible for compute, networking, storage, IAM and Kubernetes, delivered through CI/CD so every environment is reproducible, peer reviewed and auditable rather than built by hand.
Engage this serviceBuilding the environment out against the design: segmentation and security groups, encryption, least privilege access and hardening baselines applied as code, so the posture can be reapplied and proven at any time.
Engage this serviceCross-cloud tradeoff analysis, platform selection, and target architecture design. Grounded in hands-on architecture across all four government clouds, with primary production depth in AWS, rather than vendor documentation.
Engage this serviceMoving estates from where they are to where they need to be, without losing data or the ability to prove what happened to it. Databases, integration and the platform patterns around them, primarily into AWS and AWS GovCloud.
End-to-end migration of legacy database estates, primarily into AWS and AWS GovCloud, with Azure Government, OCI and GCP supported where the estate requires it. Assessment, target architecture, execution, validation, and post-migration tuning, with data integrity as the non-negotiable.
Engage this serviceReplacing hand-built infrastructure and brittle point-to-point integration with automated, event-driven and containerized patterns: change data capture, streaming backbones and platforms that can be rebuilt from code.
Engage this servicePipeline engineering across heterogeneous systems at multi-terabyte scale, using SSIS, Informatica, Qlik Replicate, and custom Python, with change data capture, bulk load, and streaming patterns.
Engage this serviceEnvironments do not stay healthy on their own. Fortis runs the operational layer that keeps cloud and data platforms patched, observable, recoverable and secure, with security built into the delivery pipeline rather than checked at the end.
Pipelines for infrastructure, schema and configuration change, with plan review, approval gates and automated testing, so change becomes routine and traceable instead of risky.
Engage this serviceMetrics, logs, dashboards and alert thresholds across the platform, built so problems surface before users report them, with capacity planning driven by what the telemetry actually shows.
Engage this serviceScheduled patching and version upgrades, backup and restore verification that proves recovery works, and runbooks an on-call engineer can follow under pressure.
Engage this serviceHardening baselines, secrets handling, least privilege access and audit logging enforced through the delivery pipeline, so compliance evidence is produced by the platform rather than assembled before an assessment.
Engage this serviceThe data layer that analytics and AI depend on, then the generative AI architecture built on top of it: pipelines, caching, retrieval, lineage and access control, on the same patterns as active federal and enterprise data programs.
End-to-end generative AI platform design on AWS: Bedrock model integration, knowledge base configuration, and direct model API implementation for data-heavy applications.
Engage this serviceVector search and retrieval-augmented generation over private datasets, so model responses are grounded in your data instead of invented. Embedding strategy, chunking, and evaluation included.
Engage this serviceDesign and deployment of agent architectures for multi-step reasoning over operational data, with action groups, tool definitions, and guardrails that keep behavior inside policy.
Engage this serviceOCR pipelines that turn physical documents into structured database records, plus image analysis with confidence scoring for inspection and asset workflows.
Engage this serviceCache-aside architecture with Redis and ElastiCache, key design for access pattern rather than habit, and invalidation strategy that stops stale data from being served confidently.
Engage this serviceCodePipeline and CodeDeploy automation for model-backed systems, identity and access architecture, environment separation, and the observability to know when behavior drifts.
Engage this serviceSecurity is not a separate bolt-on service. Key personnel bring experience with NIST 800-53, RMF, FedRAMP, FISMA, PCI DSS, SOX, vulnerability remediation, IAM, cloud security, audit evidence and control validation. Those disciplines shape how Fortis designs and operates the data platform and the infrastructure around it.
Most of this work does not end. These are the arrangements for an estate that needs an engineer on it continuously, rather than a project that closes. Fortis also supports federal programs and prime contractor delivery teams under the same model, as a scoped engineering workstream rather than staffing. Federal and prime support
A senior engineer on your database and cloud estate every month, without the cost or the hiring cycle of a full-time role. Proactive maintenance, patching, performance work, change review, and someone who already knows the environment before something goes wrong.
Discuss a retainerA block of hours drawn down as needed, for teams that have the capability in house most of the time and need depth occasionally. No monthly commitment, no minimum draw, and the hours do not expire.
Discuss availabilityRoot cause analysis and remediation when a production database or platform is in trouble: corruption, replication failure, blocking chains, a failed cutover or a failed deployment. Arranged in advance so the relationship exists before the incident does.
Set up an arrangementMost programs need more than one. Start with a fixed-scope assessment and we will propose the right approach from what it finds.