We build AI systems
that ship.

Digital Futures Consultancy LLP (UEN: T17LL1937H) is a Singapore-based AI-native consultancy founded by Steve Ng — a CISSP, CCSP, and AWS Security Specialty certified engineer. We deliver production-grade AI workflow systems for SMEs through a governed 25-agent delivery pod. Unlike traditional consultancies that deliver slide decks, we ship working systems with tests, dashboards, and documentation — then train your team to run them.

We work across six capability areas:

• AI Workflow Systems — End-to-end automated pipelines using n8n, FastAPI, and agent orchestration
• Document Intelligence — RAG, vector search, BM25, knowledge graphs, semantic retrieval
• Security Automation — VAPT, SIEM/XDR monitoring, threat detection, red/blue team tooling
• AI Strategy & Advisory — Cloud security, compliance (PDPA/GDPR), AI governance, cloud architecture
• Odoo ERP Implementation — Planning, configuration, integrations, security, training, and improvement for one connected business system
• Academy Training — Practical AI engineering and malware analysis courses, delivered online

We help businesses plan, implement, secure, and improve Odoo ERP across finance, sales, people, operations, services, websites, and productivity. The work can include discovery, a phased blueprint, configuration, integrations, testing, documentation, training, and post-go-live improvement.

The Digital Futures Academy offers three programmes:

• Practical Malware Analysis & Triage — online, part-time over 12 weeks or full-time over 6 weeks, SGD 1,200 nett
• AI Solutions Engineer Apprenticeship — online, part-time over 24 weeks or full-time over 12 weeks, SGD 3,000 nett
• AI Solutions Engineer Mastery — online, part-time over 16 weeks or full-time over 8 weeks, SGD 3,000 nett

Choose Practical Malware Analysis & Triage to build defensive malware-analysis and triage skills; the Apprenticeship if you are a career switcher, junior developer, or recent graduate; or Mastery if you are an experienced engineer or architect ready to lead production-grade AI delivery.

Three reasons:

• We ship code, not decks. Every engagement ends with a deployed system, not a PDF. 9,200 lines of code, 13/13 tests, one-command deployment — that's our standard.
• Data sovereignty by design. Self-hosted stack. Your data stays on your infrastructure. SGD 22–57/month operating cost, zero per-seat SaaS fees, no vendor lock-in.
• Speed through parallelism. Our 25-agent delivery pod works in parallel — intake, research, architecture, code gen, testing, deployment, security, docs — so we ship production systems in days, not months.

Measured ROI: 19–49× on our first deployed system (BOLDR customer intelligence engine).

Ollama Cloud is one option for accessing open models when its current provider terms and the engagement's data requirements permit it:

• Model access — It can provide access to open models through a managed cloud endpoint; review the current provider terms before use
• Local-first option — Ollama can also run locally when prompts must remain on the selected infrastructure
• Engagement-specific controls — We select the model location, data handling, and retention controls to match the business and regulatory requirements

For Singapore SMEs, this is considered alongside the organisation's PDPA obligations and risk assessment.

Our core technology engine is the 25-Agent Delivery Pod — a governed multi-agent architecture running on OpenClaw with self-hosted LLMs:

• Intake — Requirement analysis and project scoping
• Research — Domain research and data gathering
• Architecture — System design and technology selection
• Code Generation — Parallel codebase construction
• Testing — Automated e2e, unit, and integration tests
• Deployment — Docker Compose, Cloudflare tunnels, health checks
• Monitoring — Uptime, performance, alerting
• Security — PII stripping, audit logging, access control
• Documentation — Auto-generated docs, Swagger UI, runbooks
• Iteration — Feedback loop, KB gap detection, continuous improvement

Each agent has a defined role governed by human checkpoints. No data leaves your infrastructure.

The SGD 22–57/month figure is an observed operating estimate for one self-hosted AI stack's LLM API calls only; it is not a project quote. Project pricing depends on scope and complexity, while Odoo subscriptions, hosting, integrations, and Academy programme fees are confirmed separately.

Book a strategy call to discuss your specific needs and get a scoped quote.

Safety depends on the system design and operating controls. We can apply:

• Self-hosted stack — Your data stays on your infrastructure
• Local model execution — Used where prompts must remain on the selected infrastructure
• PII handling — Configurable stripping and minimisation controls
• Audit logging — Every action logged to SQLite with full traceability
• Human-in-the-loop — Sensitive actions can require explicit human approval

Provider terms and the engagement's PDPA or GDPR obligations are reviewed for each deployment.

Our 25-agent delivery pod ships production systems in days, not months. The BOLDR customer intelligence engine — 9,200 LOC, 54 files, 31 API endpoints, 13/13 e2e tests — was built and deployed in 48 hours.

Singapore SMEs across retail, e-commerce, professional services, food & beverage, and technology. Our AI workflow patterns are sector-agnostic — the classify → retrieve → draft → approve → learn cycle applies to any business with repetitive processes and growing data.

Over 80% of AI projects fail to deliver business value, and 95% of generative AI pilots show no measurable ROI. The five root causes: failure to innovate (30–50% of time lost to compliance bottlenecks), failure to scale (risk concerns choke off production), no measurable ROI (vague objectives instead of specific metrics), the "science experiment trap" (building AI for the sake of AI rather than solving real business problems), and talent/data quality gaps. Read our full analysis →

AIRPF — the AI Innovation & Rapid Prototyping Framework — is our methodology for taking an AI project from idea to demo-ready in 21 days. It fuses Design Thinking empathy, Lean Startup speed, Agile structure, ML metric discipline, and evaluation focus into a single repeatable process. Every deliverable is measurable, every sprint has accountability, and every prototype maps directly to scoring criteria. Learn more about AIRPF →

AIRPF defines success metrics in Stage 1 (Discover & Define), before code is written. We measure accuracy, latency, and human-rated empathy, then run five tests per metric with diverse inputs in Stage 4 (Validate & Measure). Every improvement is quantified so stakeholders have data to assess value.

Yes. Digital Futures is based in Singapore and serves businesses across Singapore and Asia through remote and, where practical, onsite delivery.