August 23, 2025|4:40 PM
Whether it’s IT operations, cloud migration, or AI-driven innovation – let’s explore how we can support your success.
Curious whether a focused technology shift can cut costs, speed releases, and boost customer trust all at once? We believe it can, and we build a practical path to prove it.
We combine proven playbooks, measurable outcomes, and deep experience so leaders see modernization turn into real business value. Our approach ties technical steps to revenue, margin, and resilience, while keeping mission-critical systems safe and compliant.
By aligning strategy with operating models, we create tailored blueprints that balance speed and control, and we engage stakeholders across IT, security, and the business to ensure shared success metrics. Partners like Zluri, Circular Edge, and ScienceSoft show how discovery, tooling, and governance enable repeatable wins across public cloud ecosystems.
We help companies reduce risk, right-size costs, and deliver better customer service through continuous optimization and clear execution.
We evaluate today’s leading offerings through a commercial lens, surfacing which solutions deliver cost predictability, faster deployment cycles, and stronger operational resilience.
Circular Edge emphasizes tailored strategy, secure data transfer, compliance, and post-cutover optimization to lower operational cost and improve agility.
ScienceSoft adds application and data warehouse moves, CI/CD design, hybrid integration, and managed optimization after go-live, helping teams sustain velocity.
Buyers favor firms that pair thorough discovery and roadmap design with automated execution, so agility gains are measurable without weakening compliance.
We advise buyers to prioritize transparent reporting and customer references that match their scale and regulatory profile, ensuring outcomes are predictable and aligned to business goals.
We design pragmatic roadmaps that balance speed, risk, and long‑term operational health for enterprise systems.
Core capabilities buyers should expect include discovery‑led strategy, workload assessment, and clear requirements that map business goals to technical sequencing. Teams should see CI/CD engineering, automated testing, and infrastructure as code to ensure repeatable deployments across environments.
Architecture expertise must span applications and data, from monolith modernization to microservices, and include public cloud storage, networking, and security controls. Data moves need schema evolution, quality checks, rollback plans, and documented scripts so analytics and apps remain reliable.
Buyers should shortlist firms with public cloud certifications, relevant industry experience, and verifiable references for similar applications and data scenarios.
Security must be the foundation of any transition we plan, not an afterthought that teams bolt on later. We embed identity governance, least-privilege design, and continuous controls so risk is managed as systems scale.
We use automated identity workflows to cut manual work and human error. Zluri’s discovery engine unifies identity and activity data, with 300+ connectors and 1,500+ pre-built actions. Its no-code policies and automated access reviews saved 90% of SOC 2 audit time for Assured Allies.
We map controls to auditor expectations: SOC 2, ISO 27001, HIPAA, PCI DSS, GDPR, and CCPA. ScienceSoft operates under ISO 27001 security management and ISO 9001 quality, which informs our technical and process controls.
We discover unmanaged SaaS and AI tools, correlate access with usage, and remediate risky entitlements. MFA, conditional access, hardened interfaces, and standardized baselines reduce unauthorized access and misconfiguration.
| Focus | Action | Benefit |
|---|---|---|
| Identity governance | Automated reviews, no-code policies | Faster audits, fewer errors |
| Compliance mapping | Control-to-framework documentation | Audit readiness, clear evidence |
| Shadow IT | Discovery and entitlement cleanup | Reduced exposure, centralized visibility |
We automate evidence collection and integrate approvals with collaboration tools so your team spends less time compiling reports and more time reducing risk.
We accelerate adoption with intelligent automation that enforces policies while freeing engineers for higher‑value work, creating predictable outcomes for the business and for customers.
Zluri’s adaptive automation offers customizable no‑code access policies, an extensible workflow builder, and 1,500+ pre‑built actions. These elements let teams standardize common flows without scripting, so changes are fast and auditable.
Automated reviews lighten the load on app owners and auditors, by enforcing review cycles, notifications, and stepwise remediation. Provisioning integrated with Slack reduced time-to-access from days to minutes for several customers.
| Feature | Benefit | Typical impact |
|---|---|---|
| No‑code policies | Faster policy changes, fewer errors | Minutes vs days |
| Pre‑built actions | Repeatable provisioning | 40% IT productivity gain (example) |
| Automated access reviews | Audit readiness with less manual effort | Weekly time savings for lifecycle tasks |
| Workflow integrations | Shorter time‑to‑access, better customer responsiveness | Minutes to provision via Slack |
We measure results in time saved, fewer access errors, and cycle‑time improvements, aligning automation with change management so your team owns and adapts workflows as needs evolve.
We turn complex estates into ordered workstreams, so teams move quickly while maintaining controls for cost, performance, and security.
We begin with a structured assessment that inventories applications, systems, and data, defines business and technical requirements, and prioritizes waves by risk and value.
We select the path that aligns with total cost of ownership and time constraints—rehost for speed, replatform for balanced gains, or re-architect for cloud-native benefits.
We design CI/CD pipelines with automated unit, integration, and performance testing, using infrastructure-as-code and policy-as-code to enforce consistency in public cloud environments, including Oracle Cloud where relevant.
Typical timelines range from weeks for simple applications to several months for complex apps and data warehouses; we set realistic gates and communicate dependencies to preserve momentum.
We target applications and analytics together, so teams keep features flowing while data stays accurate and available.
Our work ranges from single-app moves that show quick ROI to coordinated, multi-application programs that need shared CI/CD foundations and platform controls.
We scope single-application efforts when fast benefits matter, and larger programs where interdependencies require synchronized pipelines and staged cutovers.
We modernize architectures pragmatically, choosing containerization, managed offerings, or microservices to balance speed with long‑term maintainability.
ScienceSoft moves data warehouses using serverless ETL and scalable storage to cut consumption costs and boost query performance, including an Amazon RDS to Google Cloud analytics migration in three months.
We synchronize app cutovers with data readiness, use blue/green and feature flags for low downtime, and design observability from day one.
| Scope | Approach | Benefit |
|---|---|---|
| Single application | Fast rehost or replatform with CI/CD | Quick ROI, lower risk |
| Multi-application | Coordinated pipelines and shared platform | Smoother cutovers, fewer regressions |
| Data warehouse | Serverless ETL, scalable storage | Lower costs, better performance |
| High-load systems | Blue/green, feature flags, observability | Minimal user impact, fast rollback |
We document trade-offs and ownership so your teams can evolve systems end to end after the initial migration, delivering practical, measurable solutions.
We focus on practical cost controls that keep performance steady while shrinking operational waste. ScienceSoft cites Flexera’s State of the Cloud report showing an average of 35% wasted spend, with some estates losing more than 70%.
We combat that waste by combining right‑sizing, autoscaling, and clear cost visibility. Early tagging and instance selection match workloads to the most cost‑effective options without hurting availability.
Right-sizing and commitments ensure compute and storage align with real demand, while reserved commitments lower run rates for steady workloads.
Autoscaling policies and schedules turn fixed capacity into variable cost, scaling down aggressively during idle periods and scaling up under load.
We install dashboards and alerts that attribute spend to teams and applications, enabling showback, chargeback, and smarter engineering choices.
We anchor optimization to security and reliability, validating that savings never reduce redundancy, backups, or incident response. Our reporting translates technical gains into budget impacts executives can trust.
Selecting between a time‑boxed engagement and an ongoing arrangement affects velocity, accountability, and institutional knowledge. We help companies choose the model that balances short‑term deadlines and long‑term operations.
Ongoing managed offerings cover operations, optimization, and continuous improvement after cutover. ScienceSoft runs such programs with SLAs, regular reports, and clear KPIs so teams see measurable progress.
Those models sustain velocity by improving CI/CD pipelines, performance tuning, autoscaling, automated testing, and access management. They reduce recurring failures, tame high costs, and free internal teams to focus on product work.
Time‑boxed engagements fit data center exits, single‑app rehosts, or tightly scoped modernizations with a defined end state. They are efficient when the goal is speed, predictable budget, and a limited scope of work.
| Model | Best for | Typical outcomes |
|---|---|---|
| Project-based | Fixed deadlines, clear scope | Fast cutover, defined handoff |
| Managed operations | Continuous optimization, new workloads | Lower run costs, higher reliability |
| Hybrid | Phased programs with ops handover | Smooth transition, retained context |
We advise companies to weigh scale, risk appetite, and budget, and to include platform specialization such as Oracle Cloud when that matters for governance and compliance.
We lay out realistic timelines and budget bands so leaders can plan confidently and avoid surprises. Early discovery sets the schedule and the estimate, reducing the chance of late scope changes that inflate costs and delay delivery.
Simple applications often complete in about 2 to 2.5 months, while medium and complex apps commonly take 6+ months depending on integrations and testing depth.
Data warehouse moves vary more—expect roughly 2–8 months based on data volume, transformation needs, and chosen approach.
Reference ranges: medium/large applications typically fall between $20,000 and $250,000. Data warehouse efforts often run $140,000–$280,000 for mid-size firms and $280,000–$700,000 for larger enterprises.
| Item | Typical duration | Planning tip |
|---|---|---|
| Simple application | 2–2.5 months | Fixed scope, fast rehost |
| Complex application | 6+ months | Integrations and tests drive time |
| Data warehouse | 2–8 months | Align ETL, performance targets |
We favor clear estimates, transparent reporting, and early vendor alignment—including commercial terms for Oracle Cloud—so your team and customer expectations remain aligned.
We assess leadership by looking for verifiable experience, ISO-backed processes, and wide industry exposure that together lower program risk and speed value delivery.
Years of proven work matter: ScienceSoft brings 35 years in IT, 12 years in cloud database and application migration, and 11 years in DevOps, backed by ISO 9001 and ISO 27001. Those credentials show consistent quality and measurable security controls.
We favor teams that operate across 30+ industries—healthcare, financial services, retail, manufacturing, marketing, and telecom—because pattern recognition reduces surprises in compliance and integration.
We reference analyst outputs such as the gartner® magic quadrant™ and magic quadrant™ saas research when evaluating saas management tools. Zluri’s whitepaper on the Gartner Magic Quadrant for SaaS Management Platforms and KuppingerCole views help us verify discovery and governance claims.
| Signal | Why it matters | Example |
|---|---|---|
| Experience | Predictable execution | ScienceSoft: 12 years of migration work |
| ISO certifications | Process rigor and auditability | ISO 9001, ISO 27001 |
| Analyst validation | Independent vetting of tools | Gartner® Magic Quadrant™ references |
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We prioritize practical steps that protect production systems while unlocking efficiency and faster feature delivery.
ScienceSoft shows how end-to-end coverage, from strategy through day‑2 optimization, keeps outcomes measurable and durable. Zluri demonstrates identity governance and automation that cut audit effort and close shadow IT gaps. Circular Edge brings tailored strategy and ongoing support to future‑proof operations.
We recommend a disciplined migration process, strong governance, and targeted automation to accelerate cloud adoption while protecting budgets and uptime. Align scope, timeline, and investment with business priorities, start with focused discovery, and set measurable success criteria before execution.
Adopt an end-to-end mindset so teams inherit resilient platforms, actionable dashboards, and clear runbooks for continuous improvement.
We help achieve measurable commercial outcomes, including tighter cost control through right-sizing and autoscaling, faster time-to-market with CI/CD enablement, and improved resilience via modern architectures, while transferring operational know-how to your teams for sustained benefits.
We evaluate each application’s architecture, dependencies, performance needs, and business value, then recommend the approach that balances risk, cost, and speed—rehosting for speed, replatforming for incremental improvement, and re-architecting when cloud-native benefits justify the investment.
We design controls and reporting to meet major frameworks, including SOC 2, ISO 27001, HIPAA, PCI DSS, GDPR, and CCPA, integrating continuous compliance checks so your systems remain auditable and secure throughout the transition.
We implement identity governance and automation, enforce least-privilege access, use role-based provisioning and automated deprovisioning, and run periodic access reviews to reduce risk and close shadow IT gaps across apps and interfaces.
We deploy no-code policy engines, pre-built actions, and workflow builders to automate provisioning, compliance checks, and routine operations, enabling rapid adoption without sacrificing governance or visibility.
Yes, we handle single and multi-application migrations and large-scale data moves, including cloud data warehouse transitions and serverless ETL models, coordinating CI/CD pipelines and testing to minimize disruption.
We deliver cost visibility and reporting, implement rightsizing and autoscaling policies, and run post-migration optimization reviews to eliminate waste and align spend with business priorities.
We provide continuous managed services for evolving needs and project-based engagements for time-boxed efforts; choose managed services when you need ongoing optimization and governance, or a project model when you have a defined scope and timeline.
Timelines vary by workload complexity—simple rehosts can complete in weeks, complex re-architectures in months—while costs depend on scope, data volume, and compliance requirements; we provide tailored estimates after a rapid assessment.
We embed documentation, run hands-on workshops, and incorporate CI/CD and operational runbooks into the engagement, ensuring your staff can operate and evolve systems post-handover with confidence.
Look for proven experience across industries and public cloud ecosystems, relevant certifications such as ISO and security attestations, published case studies, and recognition in analyst research like the Gartner Magic Quadrant for SaaS management to validate capabilities.
We identify unmanaged systems, prioritize remediation by risk, apply governance controls and automated access management, and work with business owners to replace shadow tools with compliant alternatives that meet user needs.
We support migrations across major public cloud ecosystems, including Oracle Cloud, AWS, Azure, and Google Cloud, tailoring architecture and tooling to each platform’s strengths while maintaining consistent governance and cost controls.
We track KPIs such as cost savings, application performance, deployment frequency, downtime reduction, and compliance posture, delivering regular reports and recommendations for continuous improvement.
