SDLC Automation and AI-Assisted Engineering

Build faster, safer software delivery systems with practical automation.

Bakalar Software helps organizations modernize software delivery through SDLC automation, AI-assisted engineering workflows, agent orchestration, and enterprise-friendly architecture implementation.

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How it works

Every change follows the same governed pipeline

Ticket Input

AI Plan Structured proposal

Approve Plan Human checkpoint

AI Code Full implementation

Approve Code Human checkpoint

Build + Audit Verified & recorded

Two human checkpoints. No exceptions.

Why Bakalar Software

Practical engineering mindset grounded in implementation detail.
Architecture-driven approach aligned with real system constraints.
Enterprise realism across governance, security, and rollout complexity.
Focus on usable systems, not short-lived demos.

Who It's For

Regulated industries — banks, healthcare systems, insurance platforms, and government contractors operating under SOC2, HIPAA, or ISO 27001.
Engineering leaders who need consistency across teams that include junior developers, contractors, or anyone unfamiliar with the codebase.
Teams burned by autonomous AI tools — who want the speed of AI-generated code without surrendering control over what runs in production.
Teams coordinating multiple developers — engineering leads who need dependency ordering, conflict detection, and a shared audit trail across parallel workstreams.

Multi-Developer Coordinator

Scale from one developer to a whole team

The companion sdlc-coordinator.jar sits above the per-developer pipeline. It decomposes a goal into a dependency-ordered task graph, enforces prerequisite ordering before any task can start, and detects file conflicts across concurrent developers — before they become merge problems.

Every assignment, completion, conflict, and resolution is appended to an event-sourced audit log. The full team state is always derivable by replay — and always auditable.

See the coordinator →

# Decompose a goal into a task graph
$ java -jar sdlc-coordinator.jar decompose \
    --goal "Add OAuth2 authentication"

  TASK-01  Add token validation middleware      PENDING
  TASK-02  Add /auth/login endpoint            PENDING  [needs TASK-01]
  TASK-03  Add /auth/refresh endpoint          PENDING  [needs TASK-01]
  TASK-04  Update integration tests            PENDING  [needs TASK-02, TASK-03]

# Assign tasks — prerequisites enforced
$ java -jar sdlc-coordinator.jar assign \
    --task TASK-01 --developer gordan
$ java -jar sdlc-coordinator.jar assign \
    --task TASK-02 --developer nadan

# TASK-02 is blocked until TASK-01 is verified
  [WARN] TASK-02 prerequisite TASK-01 not yet VERIFIED

SDLC Automation

A governed, two-checkpoint pipeline: ticket in, plan reviewed, code reviewed, build verified, audit written. Every AI-assisted change follows the same enforced process.

AI-Assisted Development

Embed AI-assisted software development practices while preserving engineering standards and safety.

RAG and Context Systems

Implement retrieval-augmented context so systems can reason over code, architecture, and standards.

Developer Productivity Tooling

Build practical tools that eliminate repetitive engineering work and improve throughput.

Enterprise Architecture

Translate strategy into delivery-ready architecture with measurable and realistic rollout plans.