Swimm

Overview

Swimm provides "agentic modernization" services, combining static analysis, generative AI, and human expertise to help organizations with complex software modernization projects. Their offerings focus on transforming legacy codebases, extracting business logic into APIs, and creating AI-ready knowledge bases. Swimm aims to deliver accurate, complete, and on-time modernization outcomes for challenging technical environments.

Key Features

• Deterministic Analysis — Proprietary engine maps dependencies, data flows, and cross-repo relationships to establish a structural foundation.
• AI for Scale — AI agents, anchored by static analysis, apply verified patterns across codebases to accelerate analysis and workflows.
• SME and AI Expert Validation — Senior engineers and AI experts validate automated outputs, adding human-specific knowledge and catching nuances.
• Live Customer Workspace — A centralized platform provides visibility into project scope, progress, findings, and deliverables.
• Fixed-Price, Staged Engagements — Modernization projects are broken into four fixed-price stages (Assessment, Specification, Modernization, Enablement) with validation at each step.
• Legacy and Mainframe Coverage — Supports modernization of legacy systems, including COBOL, JCL, PL/I, and modern languages.
• Security and Deployment Flexibility — Offers SOC 2 and ISO 27001 compliance, on-premise deployment options, and customer-managed LLMs.

Who It's For

Swimm targets organizations grappling with large, complex, or legacy codebases that require significant modernization efforts. This includes enterprises needing to extract business logic from monolithic applications, migrate to API-first architectures, or prepare their codebases for advanced AI development tools. Their services are particularly suited for environments where traditional modernization approaches have failed or are deemed too risky.

Notable Strengths

Swimm's approach uniquely integrates deterministic static analysis with generative AI and human expert validation, addressing the limitations of each method when used in isolation. They offer a structured, fixed-price engagement model with clear validation points at each stage, mitigating the "all-in bet" risk often associated with large modernization projects. Their ability to deploy in secure, air-gapped, and customer-managed LLM environments, alongside support for mainframe and legacy languages, demonstrates a strong capability for handling highly sensitive and challenging technical contexts.