Core Engineering • AI Enablement • Managed Reliability

Modernize critical systems. Introduce AI with governance. Improve reliability continuously.

ARCelerators helps enterprise teams modernize backend platforms, embed AI into existing operating environments, and sustain reliability improvements through ongoing engineering support.

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Modernization
Core platform upgrades with controlled delivery and lower migration risk.
AI Enablement
AI embedded into internal systems with governance, access control, and auditability.
Reliability
Ongoing support, tuning, and operational improvement through a retained model.

How we work

  • Enterprise delivery grounded in phased execution and rollout safety
  • Architecture decisions shaped by integration depth, data complexity, and operating risk
  • AI initiatives governed through access control, auditability, and evaluation
  • Improvement programs measured through delivery, reliability, and support metrics
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Capability highlights

Focused capabilities across modernization, applied AI, and operational reliability.

Core Engineering Modernization

  • Move from monoliths to cloud-native services with staged modernization
  • Strangler-fig migrations with contract testing and traffic shadowing
  • Dual-run parity validation before cutover to reduce production risk
  • Target architecture, domain boundaries, and migration rollback paths
  • Security, observability, and data-access controls built into delivery

AI Enablement for Existing Systems

  • Internal knowledge search over docs, SOPs, and tickets
  • AI support assistants for operations and internal teams
  • AI-assisted analytics summaries
  • AI automation around alerts, incidents, and reports
  • Integration, guardrails, access control, and auditability

Managed Reliability & Continuous Improvement

  • Monthly support and targeted enhancements
  • Performance and cost tuning
  • Observability and incident reduction
  • AI workflow monitoring
  • Predictable, retainer-based delivery cadence

A delivery model designed for enterprise change

Structured to reduce execution risk while keeping modernization, AI adoption, and operational improvement measurable.

01

Diagnose

Assess architecture, delivery friction, operational constraints, and the risk profile of the current estate.

02

Modernize

Advance services, integrations, and data movement through phased execution and controlled cutover.

03

Enable AI

Introduce AI into internal workflows with retrieval, permissions, evaluation, and governance controls.

04

Retain & Improve

Establish an ongoing cadence for support, tuning, monitoring, and reliability improvement.

Services & Offerings

Structured offers designed to reduce operational risk, accelerate delivery, and support ongoing modernization.

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Offer 1

Modernization & Reliability Assessment

A two-week assessment that identifies the safest modernization path without disrupting operations.

For

Manufacturing plants and enterprise IT teams with legacy MES/ERP integrations, brittle data flows, slow releases, and recurring production-impacting incidents.

Outcome

A clear, prioritized plan to modernize safely without disrupting day-to-day operations.

Included

  • Architecture and integration review across MES, ERP, SCADA, IoT gateways, APIs, and batch jobs
  • Data flow review across stream and batch pipelines, historians, warehouses, and quality data
  • Performance and availability risk mapping, including bottlenecks and single points of failure
  • Observability gap analysis across metrics, logs, traces, alerts, and incident readiness
  • CI/CD and release process review, including test coverage, environments, and rollback strategy
  • Security basics review covering access patterns, secrets handling, and audit/logging readiness

Offer 2

Delivery Acceleration Sprint

A four-to-six week sprint that ships one production-ready modernization slice while establishing safer delivery practices.

For

Teams that need a fast, tangible improvement with minimal operational risk and a clear path to production.

Outcome

Ship a modernization slice and establish a practical golden path for ongoing delivery.

Included

  • Refactor or extract one critical service or module using a strangler approach
  • Stabilize one key pipeline such as telemetry, quality data, or production reporting
  • Add parity and integration tests with safer release controls such as feature flags
  • Implement structured logging, trace correlation, metrics, dashboards, and alerting for critical flows
  • Improve latency, reduce data-loss risk, and prepare a production rollout plan with rollback safety
  • Establish a CI/CD baseline for build, test, and security checks around the selected slice
  • Create operational handover notes so the team can support the new flow after rollout
  • Define a practical golden path that can be reused for the next modernization slice

Offer 3

Managed Engineering Retainer

A monthly retained model for continuous stability, incremental modernization, and steady operational improvement.

For

Plants and enterprise IT teams that need continuous stability and modernization without building a large in-house platform team.

Outcome

Predictable delivery, reduced incidents, and ongoing modernization through a structured operating cadence.

Included

  • Production support during business hours, including bug fixes and minor enhancements
  • Monthly health reporting covering KPIs, operational risks, and prioritized backlog items
  • Incremental modernization work, including one to two focused epics per month where appropriate
  • Performance and cost optimization, plus proactive reliability work such as SLO tuning and incident prevention
  • AI workflow pilots integrated with core systems, including SOP search, incident summaries, and ticket triage where relevant
  • Evaluation and guardrails for grounded answers, access control, and quarterly architecture roadmap refresh

What this means for your team

Three focused service lines aligned to modernization, controlled AI adoption, and long-term operational resilience.

  • Modernize with control — evolve backend platforms and data flows through staged delivery models that reduce operational and migration risk
  • Apply AI where governance matters — embed AI into internal systems, knowledge sources, and workflows with access control and auditability
  • Improve reliability as an operating discipline — convert support, performance tuning, and observability into a sustained improvement program
  • Operate within enterprise realities — architecture complexity, security review, compliance expectations, and rollout safety are treated as first-order concerns
  • Start from the highest-value constraint — engage around modernization, AI enablement, or retained reliability support based on the most immediate operational bottleneck
  • Keep delivery tied to measurable outcomes — scope is anchored to release confidence, incident reduction, support efficiency, and operating performance
  • Create a path for expansion — modernization engagements can extend naturally into AI enablement and ongoing reliability stewardship
  • Support clearer decisions — each service line is specific enough for technical and executive stakeholders to evaluate with confidence

Why ARCelerators?

Engineering depth, governed AI adoption, and a disciplined approach to operational improvement.

Deep backend credibility

Core modernization work is anchored in backend systems, event-driven architectures, databases, and demanding performance constraints.

AI with integration and guardrails

AI is applied within existing systems and operating workflows, with governance, traceability, and measurable business value.

Recurring improvement engine

Retained support converts reliability, tuning, and enhancement work into a repeatable operating model rather than a series of one-off interventions.

Representative engagements

Illustrative examples of the types of work these engagements are designed to support.

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Reduced release risk · improved latency · completed migration

Legacy core platform modernization

Modernization of Spring Boot services, Kafka integrations, and Oracle-to-PostgreSQL data migration through a staged cutover program.

Faster resolution paths · fewer manual escalations · auditable AI outputs

Internal AI enablement

Internal knowledge search and support assistance connected to SOPs, tickets, and documentation with governed access control.

Lower incident volume · improved cost profile · monthly improvements delivered

Managed reliability retainer

Ongoing observability, performance tuning, enhancement delivery, and AI workflow monitoring for a business-critical operations platform.

Frequently asked questions

How do you approach core engineering modernization safely?

We use phased delivery, test harnesses, migration sequencing, and controlled cutovers so backend and data changes remain reversible, measurable, and operationally safe.

Do you build AI chatbots?

Our focus is on AI embedded in internal systems and workflows, supported by retrieval, permissions, auditability, and clearly defined operating metrics.

What does the managed reliability retainer cover?

The retainer typically includes monthly support, targeted enhancements, observability, performance and cost tuning, incident reduction, and monitoring for AI-enabled workflows.

How do you measure success?

We define success measures at the outset, including release confidence, latency, incident rate, support load, automation gains, and business outcomes aligned to the engagement.

Discuss the right starting point

We can help identify the right entry point based on architecture complexity, support pressure, delivery risk, and operating goals.

View representative engagements

Your request will open an email draft addressed to contactus@arcelerators.com.