Founder-led software research company · Founded 2026 · Research-stage
Kalu Kode builds an evidence layer for four difficult moments in software: preserving a deployed application, recovering maintainable source from what shipped, remembering why the code became what it is, and keeping AI-driven changes inside a controlled process.
Four products. One evidence philosophy.
KodeCapture preserves the deployed truth, KodeBack turns that truth into an editable recovery workspace, KodeAtlas preserves the development memory around the code, and KodeProof controls future AI-assisted changes. Each product stands alone; together they form a continuous evidence system.
Capture routes, assets, requests, storage, runtime signals, and replay boundaries as a reusable evidence workspace for authorized engineering work.
Explore KodeCaptureAuthorized teams can capture a deployed application, recover an editable candidate, identify dependencies and protected contracts, and report what is supported by evidence—and what is not.
Explore KodeBackPreserve Git and GitHub evidence today, then connect symbols, history, planned work, risk, and active-agent context as the platform evolves.
Explore KodeAtlasTurn a risky refactor into an isolated, declared transaction with bounded decisions, deterministic actuators, layered evidence, and controlled transfer.
Explore KodeProofWhy Kalu Kode exists
A business may still depend on an application even when its deployed behavior is poorly preserved, the repository is missing or stale, or a vendor handoff failed. At the same time, coding agents can make changes faster than teams can confidently review them.
Both problems create the same gap: the result may look plausible, but the evidence needed to trust it is missing. Kalu Kode is building that missing layer.
Operating principles
Each principle is a product boundary, not a brand sentiment.
A clean diff, a passing build, or a confident model response is not enough by itself. Trust should be tied to observable facts, declared scope, and reproducible checks.
When a fact or edit can be established mechanically, the system should own it. Models should be reserved for the decisions that actually require judgment.
An agent may decide what a symbol represents or which reviewed option is best. It should not silently widen scope, mutate protected surfaces, or skip required validation.
A useful system says what was recovered, what was checked, what remains unresolved, and where evidence is weak. Uncertainty is better than false green.
How the platform compounds.Every hard case should become a stronger artifact, fixture, or contract—not disappear into a chat transcript.
Explore researchResearch beneath and beyond the product line
These are active capability areas and working names, not independently launched products.
Identify what third-party, generated, and authored code actually shipped—even when manifests are stale or unavailable—and keep uncertainty visible.
Help authorized teams understand which logic, dependencies, routes, and sensitive assumptions are recoverable from shipped client artifacts—and what should move behind server authority.
Connect visible UI, runtime objects, scene nodes, and WebGL evidence back to likely source locations so engineers and agents can work from the thing they see.
We publish what the systems can support, where they fail, how the evidence is collected, and which claims remain unproven. Owned demonstrations and synthetic experiments are labeled as such.
Kalu Kode is pre-revenue and has not validated market fit. We are looking for organizations with real, authorized capture, recovery, or AI-refactor problems.
KodeProof cannot use its own verdict as the sole proof that it works. We need frozen campaigns, independent graders, calibrated mutations, and reports that include false blocks.
Our recovery system evolved by removing one false assumption at a time: permanent opacity, reconstruction from description, recovery-shaped workspaces, and broad agent handoff.
Founder-led and bootstrapped
Kalu Kode was founded in 2026 by a full-stack software engineer with more than 16 years of industry experience. The company is founder-led, with AI agents used to accelerate engineering inside the same evidence and control systems the products are designed to provide.
Meet the founderWork with Kalu Kode
Need to preserve a deployed application, recover software you own or are authorized to inspect, or evaluate a risky AI-driven refactor? We are opening a limited number of early-access, assessment, and private-alpha conversations while the products remain in research.
