Critical databases need a dependable operating team
Add monitoring, incident ownership, maintenance, and senior DBA capacity around your existing team.
Oracle · SQL Server · PostgreSQL
Managed database services for mission-critical systems.
Keep critical databases reliable. Datrick provides senior-led operations, migration, performance tuning, and recovery for technology teams and IT service partners. Build AI on a dependable data foundation.
5+ years of recurring partner delivery
On-premises and cloud migrations
US-incorporated · Senior-led · Global delivery
- Operate
- monitoring, incidents, maintenance, technical ownership
- Migrate
- assessment, conversion, validation, cutover, hypercare
- Improve
- performance, recovery readiness, reliability, AI data access
Database delivery model
Senior-led
Managed services
Accountable operations
Monitoring, maintenance, incident response, runbooks, and named technical ownership
Migration
Controlled cutovers
On-premises to on-premises or cloud, with validation, rollback, and operating handover
Reliability
Performance and recovery
Query tuning, capacity review, backup verification, and high-availability readiness
AI data infrastructure
Reliable data for AI
Governed access, trusted pipelines, retrieval, and monitored production integrations
When teams bring us in
Database expertise when continuity, capacity, or a migration is at risk.
A platform move needs a controlled cutover
Plan dependencies, database development, reconciliation, rehearsal, rollback, and post-migration support.
A critical database loses its technical owner
Recover access, establish the baseline, stabilize operations, and create a documented ownership path.
An IT service firm needs DB developers and DBAs
Add accountable specialist delivery under your brand while retaining the client relationship.
Delivery capabilities
Operate, migrate, and strengthen your database estate.
Managed Database Services
Oracle, SQL Server, and PostgreSQL monitoring, maintenance, incident response, documentation, and accountable DBA ownership.
Database Migration and Modernization
On-premises to on-premises and cloud migrations, SQL conversion, data validation, cutover preparation, and hypercare.
Database Reliability and Performance
Performance tuning, capacity planning, high availability, backup verification, and disaster recovery readiness.
DBA Support and Coverage
Scope business-hours or 24/7 coverage around your critical workloads. Staffing, on-call duties, response targets, and escalation are agreed in writing.
Database delivery evidence
A delivery relationship built over 5+ years.
The right starting point should produce evidence, reduce operating risk, and make the next decision easier. These are verified examples, published only at the level confidentiality allows.
Review the evidence standard and anonymized cases
Reporting warehouse
68% faster queries
- SituationSlow, scan-heavy reporting workloads.
- DeliveryQuery, model, and scan-behavior optimization.
- Outcome68% faster queries and 85% lower scan volume.
Recurring partner delivery
Initial delivery expanded into 5+ years of work
- SituationAn IT service firm needed dependable delivery behind its client relationship.
- DeliveryDBA/NOC, migration, BI, reporting, and analytics support.
- OutcomeReliable delivery led to repeat work across additional services.
Confidential AI delivery
Expert review for leading AI model programs
- SituationTechnical evaluation required judgment across code and data.
- DeliveryRubrics, reference answers, SQL, analytics, and model-output review.
- OutcomeRepeatable confidential delivery across technical disciplines.
Why Datrick
Production ownership that continues beyond the project.
A named senior lead
Technical decisions, risks, delivery standards and communication have an accountable owner.
Meet the technical leadOracle, SQL Server and PostgreSQL
Choose the operating model and migration destination that fit the workload, dependencies and budget.
Explore database servicesRecovery and change are planned
Agree access, monitoring ownership, restore evidence, escalation and rollback before critical changes.
Review recovery servicesBuilt for long-term partnership
A 5+ year service-firm relationship grew from database delivery into ongoing operations, BI and analytics.
Read the partner case studyDatabase expertise
Senior ownership across Oracle, SQL Server, and PostgreSQL.
Oracle Managed Services
Database health, SQL performance, backup and recovery, replication, availability, and migration planning.
SQL Server Managed Services
T-SQL development, query tuning, job reliability, backups, high availability, and on-premises or cloud transitions.
PostgreSQL Managed Services
Query and index tuning, maintenance, replication, restore verification, migration validation, and production support.
Start with the operating need
Assess the risk. Deliver the change. Own the operations.
Database Health Assessment
Understand performance, recovery, coverage, and ownership gaps before committing to a support model.
- Produces
- Operating baseline and prioritized improvement plan
- Scope
- Agreed platforms, environments, and access
Database Migration Delivery
Bring senior DB developers and DBAs into assessment, conversion, validation, rehearsal, cutover, and handover.
- Produces
- Defined workstreams, acceptance criteria, and rollback plan
- Scope
- On-premises and cloud destinations
Managed Database Operations
Establish ongoing monitoring, maintenance, incident handling, reporting, and senior technical ownership.
- Produces
- Named responsibilities, runbooks, and service reporting
- Coverage
- Hours and response targets agreed before onboarding
AI built on reliable data
Extend your database foundation into dependable AI.
AI Data Infrastructure
Trusted pipelines, governed data access, reliable source systems, and clear ownership for the data your AI depends on.
AI readiness and model selection
Compare use cases and models against business value, data readiness, security, integration, and operating cost.
AI implementation and evaluation
Integrate workflows with representative evaluations, human review, production controls, and ongoing support.
Datrick AI Decision-to-Operations Framework
Six decision gates from opportunity to dependable operations.
Each gate resolves a specific executive or operating question, produces reviewable evidence, and ends with an explicit decision before more investment is committed.
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01
Value
Where can AI create measurable value?
Prioritize workflows against baseline effort, quality, capacity, revenue, risk, and adoption.
Evidence: use-case and ROI scorecard -
02
Model fit
Which technical route fits the work?
Compare model and automation options using representative tasks, constraints, and total operating cost.
Evidence: model selection record -
03
Readiness and risk
What must be ready before delivery?
Expose gaps across data, integration, security, governance, ownership, evaluation, and adoption.
Evidence: readiness and risk register -
04
Pilot evidence
Does the workflow work under realistic conditions?
Test bounded scope, representative scenarios, users, failure modes, controls, and acceptance criteria.
Evidence: pilot decision package -
05
Production controls
Can the workflow operate safely and reliably?
Add access control, observability, human review, fallback, auditability, documentation, and ownership.
Evidence: production readiness record -
06
Managed operations
How will quality and value hold over time?
Monitor service health, model behavior, cost, incidents, data dependencies, adoption, and improvement work.
Evidence: operating baseline and cadence
Institutional trust register
Four claims a buyer can trace before starting a conversation.
Datrick separates company identity, ecosystem position, named accountability, and delivery evidence so each can be reviewed on its own terms.
- Corporate identity
- Datrick, Inc. Delaware corporation with operating presence in Wilmington and Istanbul. Review company structure
- Named accountability
- Can Goktug Ozdem Founder and senior technical lead responsible for scoping, delivery standards, and technical review. Review leadership
- Ecosystem position
- Claude Partner Network participant Claude implementation and enablement connected to production data, controls, and operating ownership. Review Claude capability
- Evidence standard
- Claims stay bounded Measured outcomes, operating outcomes, and confidential delivery are labeled separately. Review delivery evidence
AI engagement paths
Choose the smallest engagement that resolves the next decision.
Each path has a defined decision, evidence standard, and commercial boundary. Start where uncertainty is highest, then expand only when the evidence supports it. If you are comparing implementation partners, use the AI consulting RFP and vendor selection checklist to normalize proposals.
AI Decision Sprint
For one priority workflow when the value case, model route, readiness, or responsible pilot scope is still unclear.
- Produces
- Value case, model evidence, risk register, and pilot charter
- Investment
- $15,000 fixed scope
- Typical duration
- 2 weeks
Production AI Pilot
For a bounded workflow that must prove quality, integration, controls, user fit, and operating viability under realistic conditions.
- Produces
- Working pilot, evaluation baseline, controls, and decision package
- Investment
- Scoped to workflow and evidence requirements
- Boundary
- Defined acceptance criteria before implementation
Managed AI Operations
For production AI workflows that need accountable ownership across quality, incidents, model changes, cost, releases, and improvement work.
- Produces
- Operating baseline, service cadence, reporting, and prioritized backlog
- Investment
- From $15,000 per month
- Boundary
- Ownership and service scope agreed before transition
AI delivery
Claude Partner Network participant
From expert model evaluation to governed Claude workflows.
Datrick combines production data experience with confidential leading-model training work. We help AI teams improve technical quality and help enterprises put Claude into controlled operations.
If the use case or platform is still unclear, start with a vendor-neutral AI readiness assessment and model selection before funding implementation.
Technical model evaluation
Coding, SQL, data, analytics, rubrics, reference answers, and model-output review.
Claude workflow implementation
Internal assistants, document intelligence, data copilots, reporting, and operational automation.
Governance and production rollout
Evaluations, access controls, logging, human review, fallbacks, documentation, and support.
Engagement model
Structured enough for enterprise buyers, lightweight enough to start quickly.
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1
Written scoping
Share the situation, systems, risks, prior attempts, and timeline.
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2
Delivery plan
Define ownership, access, deliverables, escalation, and acceptance.
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3
Senior delivery
Execute through a named lead with visible status, findings, and decisions.
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4
Continuity
Document the work, transfer knowledge, and define ongoing support where useful.
Contact
Start with the smallest useful step.
Describe what is happening, what is at risk, and what has already been tried. A senior lead will review it and recommend the right next step within one business day.
Planning ranges
A useful starting point, not a rigid package.
Every situation is different. These ranges are here to help with early planning; after review, we recommend the smallest scope that can produce a useful outcome.
- Database assessment
- Scoped to estate and risk
- Database migration
- Scoped to workstreams and cutover
- Managed database services
- Monthly scope and coverage agreed
Urgent support is prioritized after written intake. Final pricing reflects risk, access, response time, and delivery ownership.