Experts across every technology.
AI-native at the core.

Founded in 2026, we are deliberately new — but our founders, senior consultants, and partner network bring decades of enterprise technology experience across AI, data, cloud, application, and enterprise platforms. "New company" is a feature: we are AI-native by design, not retrofitted from a legacy services model.

We work transparently. We never claim partnerships we don't have. We will never put a face on a slide that won't sit on your call. Risk is reduced through partner-led delivery, AI-native curation, unified governance, and the option to start small before scaling.

Staffing firms sell hours. Consultancies sell decks. We provide the right experts and teams across every technology — found and curated by AI-native sourcing, governance-aware, and designed for insourcing into your organization. AI & data are the core every engagement is built around, but we cover the full technology spectrum. We are a broad-spectrum technology capability partner, not a staffing company.

Two things. (1) Our internal & sourcing systems are AI-native — we use AI to identify, curate, and match right-fit experts to each customer's exact requirement, at a scale and speed manual search can't match. (2) AI & data are the core every engagement is built toward, so the technology we deliver today is ready for tomorrow's productivity. We don't just deliver AI — we run on it.

No. AI & data are our core strength and the hook — but we provide experts across every technology: application engineering, cloud & platform, enterprise apps (SAP, Salesforce, ServiceNow), integration, cybersecurity, quality engineering, and more. Because our sourcing is AI-native, we occasionally supply experts even in non-IT domains — under 5% of our professional services. Whatever the technology, we deliver it with AI & data as the core for future readiness.

No. We are not a hyperscaler, model vendor, or product reseller. Our product portfolio is partner-led, focused on AI & data, accessed as capabilities. We provide expertise across the major clouds (AWS, Azure, GCP), data platforms (Snowflake, Databricks), AI providers (OpenAI, Anthropic, Mistral, open-source models), and the wider technology stack. Product access is enabled through our product principals under our unified governance — and you own everything we help you build. Crucially, where a partner-led product touches your data, the product principal's own certifications and regional data-residency commitments apply, with CyberSpark governance verifying them on top (see data & residency below).

Pre-vetted specialists from our virtual bench typically deploy in days, not months. Larger Capability Units (5–25 people) typically stand up in 4–8 weeks, depending on governance, security clearances, and the depth of capability design required. The mobilization milestone in every contract makes this explicit so there is no ambiguity about when capacity becomes productive.

Two layers. First, the people-and-capability milestones above — mobilization, productive capacity, stabilization, knowledge transfer, ownership transition. Second, outcomes the team is responsible for, agreed jointly with your sponsor: production deployments, time-to-decision improvements, governance posture, model evals, adoption metrics. We report both layers transparently on a monthly cadence.

You do. Code, models, prompts, evals, documentation, runbooks, decision logs — all of it is your IP under your engagement terms. Our role is to architect, mobilize, and operate the team that produces it, then transfer ownership of the capability when your organization is ready to run independently.

Practitioner replacement is governed at the unit level, not the individual level: if a person is not the right fit you tell us, and we replace them inside a defined window without you absorbing the ramp cost. If your priorities change and you need to ramp the unit down or pivot composition, the monthly commercial model accommodates that with pre-agreed notice terms — you are not locked into a fixed-scope commitment that no longer reflects reality.

Financial Services, Healthcare & Life Sciences, Supply Chain & Logistics, Public Sector, Telecom, Retail, and Energy. Our delivery model is industry-agnostic; our domain SMEs make engagements context-aware and regulation-aware.

We are deliberately not a fixed-cost project shop. What we deliver is the right experts and teams — individually and as complete units — architected for your environment. We’re accountable for capability and capacity milestones (mobilization, productive capacity, stabilization, knowledge transfer, ownership transition) and for jointly-agreed outcome measures; you own ultimate delivery and direction. Four engagement shapes, nested inside our three motions:

• Capability Units — complete teams designed, mobilized, stabilized, and transferred to your ownership. Monthly subscription; milestones tied to mobilization, stabilization, and transfer events.
• Talent Pods — skill-clustered groups (data engineering, GenAI enablement, etc.) sized to the outcome. Monthly subscription; milestones tied to delivery cadence.
• Insourcing Hires — individual senior or leadership roles, curated by AI-native sourcing and insourced into your team, where capability depth matters more than volume.
• Elastic Capacity — senior practitioners embedded inside your platforms and rhythms, sized to demand.

Across all four, our milestones are people-and-capability milestones — mobilization, ramp, productive capacity, knowledge transfer, ownership transition — not fixed-scope deliverables.

Correct. We have seen too many fixed-scope agentic-AI engagements collapse under change — the technology, the use cases, and the regulatory backdrop all move too fast for that model to fairly serve either side. Instead, we provide capacity and capability — the people — governed by clear outcomes, monthly cadences, and pre-agreed transition events. You always know what the team is doing, what they are accountable for, and when they ramp down or transfer.

Commercials are typically a monthly subscription per Capability Unit, Talent Pod, or individual practitioner, with clear ramp-up and ramp-down terms. Milestones are people-and-capability milestones:

• Mobilization milestone — team named, onboarded, accessing your environments
• Productive-capacity milestone — team operating at agreed throughput inside your governance
• Stabilization milestone — patterns documented, runbooks in place, knowledge codified
• Knowledge-transfer milestone — your team able to operate without our presence on critical paths
• Ownership-transfer event — final hand-off; we step back or move to a lighter advisory mode

For specific delivery work inside the engagement, we agree on outputs (architectures, models, pipelines, features) with your team — but the commercial unit remains capacity, not scope.

Engagement-by-engagement controls: data residency aligned to your region (SG, EU, US, ANZ as needed), client-tenant isolation, BYO-cloud, prompt-injection & PII guardrails by default, model-card and lineage documentation, and policy-as-code for AI usage governance. We embed Responsible AI specialists where the risk profile warrants it.

Two levels of assurance, because our product portfolio is partner-led. (1) Our people-led delivery happens inside your environment — your cloud, your IAM, your audit trails — so we hold no parallel copy of your data. (2) Where engagements use partner-led products, data residency and compliance are governed by the product principals' own certifications and regional data-residency commitments (in-region tenancy, SOC 2 / ISO posture), with CyberSpark's unified governance contracting to and verifying those commitments on top. You get the principal's assurances and ours — never ours substituting for theirs.

The team continues to operate within your organization on your contracts and rhythms. CyberSpark provides an optional ongoing "capability assurance" retainer — periodic architecture reviews, talent refresh, and agentic-AI roadmap updates — but no ongoing dependency is required. Documentation, runbooks, and decision logs are yours.

Yes — and we recommend it. Most relationships start with a short discovery engagement — typically a 2–4 person advisory pod working alongside your team for 2–4 weeks to map the capability gap and co-design the right team shape. It runs on the same capacity model as any other engagement (no fixed-scope commitment on either side) and gives both sides a low-risk way to evaluate fit before scaling into a full Capability Unit, Talent Pod, or Elastic Capacity arrangement.