Enterprise AI Capability Across Five Disciplines

From strategy through production deployment, Atlas Tech Group delivers the full spectrum of AI and cloud engineering services — with the velocity and rigor enterprise and federal clients require.

Legacy Modernization & AI Integration

Modernize Without Disruption

We help organizations replace 1990s-era ERPs, legacy mainframes, and aging line-of-business systems without operational disruption. Our strangler-fig approach progressively replaces functionality module-by-module behind a stable API surface, with pricing and business-logic parity validation against the legacy system and zero big-bang cutover risk. AI engineering is embedded throughout — accelerating module replacement, automating reconciliation, and validating parity with the legacy system at scale.

Deliverable

A modernized system that runs alongside the legacy one until parity is proven, then progressively absorbs production traffic.

Capabilities

  • Strangler-fig microservices migration
  • API-first modernization with OpenAPI 3.1 specifications
  • Multi-agent AI engineering for accelerated module replacement
  • Pricing and business-logic parity validation against legacy stored procedures
  • Partner integration architecture (scoped Bearer auth, rate-limited, audited)
  • Branch-protected CI/CD with enforced security review
  • Legacy SQL Server, Oracle EBS, and mainframe data integration

AI Systems Development

Production AI, End to End

We design and build full-stack AI systems — from data pipelines and model integration to multi-agent orchestration platforms and production deployment. Our engineering-first approach ensures what we build scales, performs, and can be maintained.

Deliverable

Production-grade AI systems ready for enterprise and federal deployment.

Capabilities

  • Large Language Model (LLM) integration and fine-tuning
  • Multi-agent AI orchestration frameworks
  • Retrieval-Augmented Generation (RAG) architectures
  • AI-native application development
  • Model evaluation and quality assurance
  • Operational AI monitoring and observability

AI Cost & Operations Engineering

Production AI That's Affordable to Operate

Production AI is only sustainable if cost is predictable. We design AI systems with quantified per-operation cost, hybrid pipelines that minimize expensive LLM calls (deterministic pre-filtering, semantic caching, tiered model selection), and operational observability that catches cost drift before it hits the budget. The result is AI features that can scale to enterprise or agency-wide deployment without surprise inference bills.

Deliverable

AI features with characterized per-inference cost, monitored consumption, and a clear path to scale.

Capabilities

  • Cost characterization per AI feature (per-inference, per-user, per-day)
  • Hybrid deterministic/LLM pipeline design for cost control
  • Model selection optimization (cheap-first, escalate-on-confidence)
  • Inference monitoring and budget alerting
  • Vendor evaluation against total cost of ownership
  • AI feature design with pre-deployment cost modeling

Enterprise Cloud Architecture

Cloud Infrastructure Built for Scale

We architect, migrate, and optimize cloud infrastructure for enterprise workloads. Our cloud engagements combine deep AWS expertise with a security-first, compliance-aware design philosophy appropriate for both commercial and federal environments.

Deliverable

Resilient, cost-optimized cloud infrastructure aligned to your security posture.

Capabilities

  • AWS architecture design and optimization
  • Cloud migration strategy and execution
  • Infrastructure-as-Code (Terraform, CDK)
  • Multi-cloud and hybrid cloud architectures
  • Cost optimization and FinOps
  • FedRAMP-aligned security controls

AI Strategy & Advisory

From AI Interest to AI Capability

We help organizations move from AI curiosity to AI capability. Our advisory engagements deliver actionable roadmaps, honest vendor assessments, and workforce enablement plans grounded in what actually works in production — not marketing slides.

Deliverable

A clear, executable AI strategy with measurable milestones and realistic timelines.

Capabilities

  • AI readiness assessments and gap analysis
  • Technology roadmap development
  • Vendor and platform evaluation
  • Build vs. buy decision frameworks
  • AI workforce training and enablement
  • ROI modeling and business case development

Federal IT & Digital Transformation

Federal Mission, Delivered

We support federal agencies and prime contractors with IT modernization, digital transformation programs, and AI-enabled service delivery. Our active SDVOSB certification and active SAM.gov registration make us a ready teaming partner for set-aside and sole-source opportunities.

Deliverable

Modern, compliant federal IT systems delivered on schedule and within scope.

Capabilities

  • Legacy system modernization and migration
  • ATO documentation and compliance support
  • Digital transformation program management
  • AI capability insertion into existing programs
  • Agile delivery for federal environments
  • SDVOSB set-aside and sole-source eligibility

AI-Accelerated Software Delivery

60–80% Faster.† Same Standards.

Our AI-assisted software delivery model compresses timelines at every phase — requirements, design, implementation, testing, and deployment — without sacrificing code quality, security, or maintainability. We use AI tooling operationally, not experimentally.

Deliverable

Working software, faster — with engineering quality that holds up in production.

† On our 60–80% claim: Reflects our own delivery experience using AI-accelerated engineering on recent Atlas Tech Group platform builds, framed against published research on AI-assisted development productivity. Independent studies have measured task-completion speedups of roughly 55% (GitHub/MIT controlled trial, Peng et al., 2023) and PR-throughput increases of roughly 39% (University of Chicago / Cursor field study, Sarkar, 2025), with PR cycle time reductions as high as 75% in GitHub's Accenture deployment. The research is not uniformly positive — METR's 2025 RCT found experienced open-source contributors took about 19% longer with AI assistance on complex codebases. Our 60–80% range describes the upper end of what we consistently see on the kind of work we take on: AI-native greenfield builds, well-defined platform components, and AI-augmented modernization. Results on any given engagement vary with codebase complexity, problem type, and how the work is scoped. For methodology questions on a specific engagement, get in touch.

Capabilities

  • AI-assisted architecture and design documentation
  • AI-augmented code generation and review
  • Automated test generation and execution
  • CI/CD pipeline design and implementation
  • Technical debt reduction and refactoring
  • Developer tooling evaluation and adoption

Ready to Get Started?

Tell us about your project. We'll respond with a clear assessment and a proposed engagement approach within 24 hours.