Ignitera Solutions is a Singapore-based, AI-native IT consultancy. Every project is led from the first call to launch by a principal engineer, heading a delivery team with AI agents in the build pipeline. We build production software for companies that have outgrown off-the-shelf tools, and we'd rather show you working progress than a slide deck.
Software engineering experience behind every line of code shipped.
Of code reviewed by a senior engineer before it ships.
Ignitera Solutions was started by an engineer who cares about one kind of software: the kind that moves a real number for the business, whether that's revenue captured, hours saved, or a customer journey that doesn't lose people halfway through. After a decade of building production systems across industries, the lesson is simple. The stack adapts to the problem, never the other way around.
Good software isn't loyal to a stack or a domain. It's loyal to the outcome the product owner is trying to reach.
We take on defined projects, not headcount. Each one is designed by the principal engineer who signs the contract, built by a team with AI agents doing the volume work, and reviewed end to end by a senior engineer.
Ten-plus years across production systems. The principal engineer owns the system design, how it's secured, and how the software fits your business goals. The same person scopes it, leads the team that builds it, and hands it over. No account managers, no escalation tiers.
AI coding agents and automated checks write the repetitive code, draft tests, generate documentation, and flag issues faster than anyone can by hand. They add speed. They don't make design decisions.
No code reaches your live system without review from a senior engineer. The agents speed up the work; the accountability for it stays with a person whose reputation is on the line.
Beliefs that show up in how a project runs, not slogans for a pitch deck.
We pick technology to fit the problem in front of us. React, Node, Postgres, AWS and serverless are the defaults we know cold, but we'll pick something else the moment a problem genuinely demands it. We're technology-agnostic and domain-flexible because that's what good engineering requires.
Big-bang releases are how projects fail quietly for six months. We work in stages, each one working, shown to you, and small enough to undo. You can stop after any phase and keep the work you've paid for.
What you buy from us is production software. AI agents are how we deliver it at this pace; they're not what we're selling. Every line still ships through human review.
If we can't see it, we can't improve it. Logging, metrics, and traceability go in on day one, so when something needs tuning, we have evidence instead of opinions.
Operating guides, a written record of the key technical decisions, and recorded walkthroughs come standard at handover. Your team should be able to operate, extend, and replace us. That's how you know the work was honest.
AI accelerates the build. It doesn't get to decide what ships. Every engagement runs a four-stage pipeline, with people in charge of the spec, the review and the release, before any code reaches your live system.
The principal engineer writes the spec. The principal engineer translates your business goal into a technical specification: system diagram, data model, security boundaries and success criteria. AI agents only ever generate code against a spec a human authored. No prompt-and-pray.
AI drafts within guardrails. Coding agents generate the code against the spec, with coding standards and security rules enforced by automated checks. Output that fails the checks doesn't reach a person. It's redrafted until it passes.↻ Fails automated checks → redrafted
Human reviews every line. A senior engineer reads every change before it's accepted, checking correctness, security, and whether it matches the spec. Automated checks run alongside (generated tests, vulnerability and dependency scans), but a person signs off.
A senior engineer oversees the release. Code goes to a test environment first and is switched on gradually, with a senior engineer overseeing the release. Monitoring is in place from day one.
The most common question we get about AI-augmented delivery is “who ends up owning what?” Here's the plain answer.
On full payment, all intellectual property in the deliverables transfers to you: source code, architecture documents, infrastructure-as-code and runbooks. If you stop after an earlier phase, the same applies to the work you've paid for. Written into every engagement contract. No licensing tricks, no vendor lock-in to us.
Our AI coding tools run with model training switched off, so your code and prompts aren't used to train models. Production data, credentials, and customer records don't go into AI tools at all; work happens against scoped, non-production contexts. If your data-residency or vendor requirements rule a tool out, we'll agree in writing what's used, and what isn't, before any code is written.
Production credentials, API keys, and customer data live in your AWS account, not ours. We work with least-privilege IAM, AWS Secrets Manager, and audit trails you can review. We can be removed from access in one revocation.
NDAs and DPAs available before the first call, not after it. We operate under Singapore's PDPA, and our privacy notice sets out how personal data is handled. For fintech and healthtech, we shape the architecture around the regime you already operate under.
We treat AI-generated code with the same scrutiny as any third-party output: dependency scanning, vulnerability checks, prompt-injection hardening for any LLM features we build into your product, and a documented threat model for AI components.
Send a few sentences on what you need built and what's holding it together today. We'll set up a 30-minute call with our principal engineer, at no charge. You'll get an honest read on whether Ignitera Solutions is a good fit, and how we'd start if we are.