Production software, shipped in iterative cuts.
Ignitera Solutions is a Singapore-based, AI-native IT consultancy. An architect-led studio with AI agents in the build pipeline — delivering production-grade software for companies and founders who want regular demoable progress, not slide decks every quarter.
Why Ignitera Solutions exists.
Ignitera Solutions exists because its engineer-founder cares about exactly one kind of software: products that measurably move a company forward. Not vanity software. Not architecture for its own sake. Software that moves a real number on a real spreadsheet — revenue captured, hours saved, a customer journey that doesn't drop people halfway through.
After a decade of building production systems across industries, one belief crystallised for the engineer-founder: a great product isn't defined by the technology behind it or the domain it lives in. It's defined by how honestly it adapts to the actual needs of the people who own it. 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.
Architect-led. AI‑leveraged. Outcome-priced.
Most consultancies sell you headcount. We sell you outcomes — designed by a senior architect, accelerated by AI agents in the build pipeline, and reviewed end-to-end by the same human whose name is on the contract.
The architect designs the system.
Ten-plus years across production systems. The architect owns the system design, security posture, and how the software aligns with your business goals. The same person scopes, decides, and hands over — no account managers, no escalation tiers.
AI agents do the volume work.
Coding agents, evals, and AI-driven QA write boilerplate, draft tests, generate documentation, and surface issues at a pace no human team can match. They compound throughput. They don't make architectural decisions.
Every line gates through a human.
No code reaches your production without review from the architect on the engagement. The agents accelerate the work; the accountability for it stays with a person whose reputation is on the line.
How we keep AI honest.
AI accelerates the build. It doesn't get to decide what ships. Every engagement runs a four-stage human-in-the-loop pipeline before any code reaches your production environment.
Architect writes the spec.
The architect translates your business goal into a technical specification — system diagram, data model, security boundaries, 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 implementation against the spec, with style guides, type rules, and security policies enforced as evals. Output that fails the evals doesn't reach a human — it gets regenerated until it passes.
Human reviews every line.
The architect reviews every diff before merge — reading for correctness, security, and alignment with the spec. AI-driven QA runs in parallel (test generation, vulnerability scanning, dependency audits), but the human signs off.
Human deploys, monitors, owns.
Code ships behind feature flags to staging first, with the architect on the deploy and on-call. Logs, metrics, and traces are in place from day one — so when something needs tuning, we have evidence rather than opinions.
Your code, your data, your IP.
The most common question we get about AI-augmented delivery is “who ends up owning what?” Here's the plain answer.
You own 100% of the code.
On full payment, all intellectual property in the deliverables transfers to you — source code, architecture documents, infrastructure-as-code, and runbooks. Written into every engagement contract. No licensing tricks, no vendor lock-in to us.
Your data isn't training fuel.
We use enterprise AI tooling under contracts that exclude your code, prompts, and data from model training. Sensitive material is scoped to private contexts; we never paste production data into public AI services.
Secrets stay in your accounts.
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.
PDPA-aware by default.
Singapore-based and PDPA-aware on every engagement. NDAs and DPAs available before a discovery call. For regulated industries (fintech, healthtech), we shape the architecture around the compliance regime you operate under.
AI vulnerabilities, mitigated.
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.
Documented to outlive us.
Runbooks, architecture decision records, and recorded walkthroughs come standard at handover. Your team should be able to operate, extend, and replace us — not because we expect to leave, but because that's what honest engineering looks like.
How we work.
Beliefs that show up in how a project actually runs — not slogans for a pitch deck.
The product adapts to the need, not the stack.
We pick technology to fit the problem in front of us. React, Node, Postgres, AWS, serverless — these are 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.
Scope tight. Ship in cuts.
Big-bang releases are how projects fail quietly for six months. We work in iterative cuts — shippable, demoable, reversible. You see progress in regular increments, and you can stop after any phase without leaving us holding code you can't run.
Outcomes first. AI is the multiplier, not the message.
What you actually buy from us: production software shipped in iterative cuts — demoable progress in regular increments, avoiding big-bang releases. AI agents are how we deliver at that pace; they're not what we're selling. Every line still ships through human review.
Instrumentation before features.
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.
Leave it documented.
Runbooks, architecture decision records, and recorded walkthroughs come standard. When we hand over, your team should be able to operate, extend, and replace us. That's how you know the work was honest.
The shape of the studio.
The future of consulting isn't bigger teams. It's smaller, sharper, AI‑leveraged ones.
For two decades, "more engineers" was the only lever consultancies pulled. It's no longer the right one. A senior architect with the right AI tooling, shipping in tight cuts under a documented review pipeline, can deliver outcomes that historically required a team. That's not a forecast — it's how Ignitera Solutions operates today.
Have something you've been trying to ship?
Send a few sentences on what you're trying to build. We'll reply with an honest read on whether we're a good fit and how we'd start.