Sigao

Service Nº 01 · Custom Software Development

More capacity won’t fix a slipping roadmap.

A senior-led Sigao team brings a proven process and an AI-native delivery platform, ships the committed work with your engineers, and leaves both behind. The roadmap moves because the way your team builds levels up, not because you added headcount.

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Built for

CTOs and VPs of Engineering with a roadmap commitment they can’t hire for in time, a product line that has to ship, or a legacy system slowing every release. You want delivery you can put numbers behind, governance built in, and capability your team owns after we leave.

What we’re hired to do

Built for the work that’s gating your date.

From greenfield product builds to roadmap acceleration and legacy modernization, including the technical debt that slows every release. One Engagement Lead owns the work start to finish. Open any engagement for the scope, the team, and how we would run it.

How engagements run

Predictable on the outside, AI-native underneath.

On the surface it looks familiar: sprints, standups, demos. What changes is how work gets defined, where AI agents sit in the lifecycle, and who answers for the quality of what ships.

  1. The people who scope it, ship it

    The senior-led team you meet in discovery is the team that writes the code. They ship to production on your stack, with your engineers building alongside them, and one Engagement Lead owns scope and quality. You get working software, not status reports.

  2. Spec-driven development

    Living, machine-readable specs are the system of record, so intent survives past any one engineer or agent. Most AI rework traces back to lost context, not weak models. Specs are how we hold the context that holds quality.

  3. Eval-driven development

    Evals, demos, and instrumentation are quality gates in the pipeline and part of the definition of done. As AI writes more of the code, more of the work becomes reviewing and validating it, so failures surface during the sprint instead of after release.

  4. AI-native, the IDE decentered

    We orchestrate coding agents across specs, prompts, and pipelines, so the IDE is one tool among several. Governance lives in the platform, not a plug-in, and nothing ships because the agent said so.

Selected work

Case studies from recent engagements.

Some named, some anonymized at the client’s request. We’ll walk through any of them on a discovery call, the rough stretches included.

  • Nº 01

    FinTech · Lending

    PE-backed loan-management SaaS

    Legacy modernization on a spec-driven agentic delivery harness

    Challenge
    A market-leading loan platform on a legacy framework — comprehensive features, dated UX, hard to maintain — under pressure to modernize faster, on a tighter budget, in a highly regulated domain where quality, security, and control can't slip.
    Approach
    Reimagined the SDLC around AI-assisted planning, design, implementation, and verification. A spec-driven process — Product Brief → Feature Plan → UX Design → Specification — supported by specialized agents, with Azure DevOps as the shared context layer and governance, guardrails, and deterministic engineering standards throughout.
    Outcome
    A repeatable agentic development harness: engineers delegate more execution to agents while keeping judgment and control, technical debt is paid down incrementally, and modernization accelerates without abandoning engineering standards. The operating model for agent-led modernization.
  • Nº 02

    Telecom & Utility Software

    Alden Systems

    Engagement · Ongoing

    Expanded delivery capacity so internal teams could focus on strategy

    Challenge
    Alden Systems, a leading software provider for telecom and utility companies, needed to expand development capacity and free its internal teams to focus on long-term product strategy — without overextending staff or compromising quality.
    Approach
    Partnered with Alden's engineering team through agile collaboration, supporting both legacy platforms and net-new feature experimentation in parallel.
    Outcome
    Consistent delivery and tight team integration let Alden move faster without compromising quality — freeing internal resources for long-term planning and making Sigao a trusted part of their ongoing growth.

    • Both supported

      Legacy + net-new

    • Freed for strategy

      Internal teams

  • Nº 03

    Nonprofit · Disability Services

    Easter Seals Greater Houston

    A custom care platform that replaced manual paperwork

    Challenge
    Easter Seals Greater Houston, a nonprofit supporting individuals with disabilities, was burdened by manual paperwork and limited visibility into client data — capping efficiency and the quality of service it could deliver.
    Approach
    Designed a custom digital solution: a web-based application portal (Angular) for families and respite-care tracking, plus a centralized admin portal (Dynamics 365) for staff to manage data, automate workflows, and generate reports.
    Outcome
    Streamlined care documentation, automated workflows, and real-time reporting — improving operational efficiency and enabling faster, higher-impact service delivery at scale.

    • Angular web app

      Family portal

    • Dynamics 365

      Admin system

    • Real-time

      Reporting

  • Nº 04

    Enterprise Software · Decisioning

    InRule Technology

    Engagement · Multi-year

    Native CRM integrations and AI features, shipped to AppSource & AppExchange

    Challenge
    InRule — a Decision Platform and business rules management (BRMS) provider — wanted to extend its ecosystem reach and introduce AI decisioning features across the major CRM marketplaces.
    Approach
    Worked hands-on with InRule's team for development, testing, and documentation — building native integrations with Microsoft Dynamics 365, Salesforce, and InRule's flagship AI decisioning engine.
    Outcome
    Successful launches on both AppSource and AppExchange and the rollout of new AI features now foundational to the product roadmap. A multi-year partnership delivering with consistency and speed through embedded agile practices.

    • AppSource + AppExchange

      Marketplaces

    • Core to roadmap

      AI features

    • Multi-year

      Partnership

What clients say

In their own words.

“These are not common staff augmentation engineers. These are people who will consider the system architecture, come up with solutions, and present options for a path forward.”

Todd Maranda

Software Architect / Security Officer

  • This was all made possible by the steadfast commitment of the Sigao team, and for that I would like to extend my utmost appreciation.

    Mark Lonsway

    Senior VP, Professional Services

  • The MVP version of the solution is nearly complete and reflects Sigao's high-quality work. They're communicative and always bring up potential delays before they become issues.

    Melissa Jakubowitz

    President & Founder

  • Working with Sigao for the first time was like flying first class for the first time. You never want to go back.

    Elise Hough

    CEO · Easter Seals Greater Houston

  • The functionality we needed for our project was not just realized but went beyond what we thought we could do with our budget.

    Cristen Reat

    Co-Founder & Program Director · BridgingApps · Easter Seals Greater Houston

Questions, answered

The questions we’d ask too.

Most of the leaders who call us have been burned by staff aug, slideware, or an AI rollout that fizzled. These are the questions that come up first.

Is this staff augmentation?
No. Staff augmentation drops contractors into your team, and the velocity leaves with them. We run the opposite model: a senior-led Sigao team runs our delivery process and writes the production code, and your engineers join that team and build alongside us. Because your people co-produce the work, they keep running the system after we leave.
Who actually does the work?
The people who scope it. The senior team you meet in discovery is the team that ships, with one Engagement Lead accountable for scope and quality end to end. No bait-and-switch, no rotating bench.
How do you use AI without lowering the quality bar?
AI is governed inside the delivery system, not bolted on. Living specs hold the context, evals and quality gates sit in the pipeline, and every change gets second-person review — nothing ships because an agent said so. As AI writes more of the code, more of the work becomes verifying it, and that verification is part of the definition of done.
Can you work inside a legacy system, or only greenfield?
Legacy is most of what we do. We modernize aging systems one proven slice at a time — mapping what the system actually does today, making it safe to change, and shipping it — while your roadmap keeps moving. We don't pitch big-bang rewrites.
What happens when the engagement ends?
The capability stays. Your team keeps the specs, the platform, the patterns, and the operating rhythm they helped build — and keeps shipping at the new speed. The lift outlasts the engagement. Many partners stay with us for years, but by choice, never by dependency.

Insights

Current thinking on shipping software.

All insights

Start an engagement

Bring us a roadmap. We’ll bring the team to accelerate it.

Thirty minutes, no pitch. We’ll give you an honest read on the work, the timeline, and the engagement model that fits. If we’re not the right team, we’ll say so, and point you toward who is.

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