For mid-market and enterprise teams moving from prototype to production. One full-time senior EIS engineer in your roadmap, FORGE methodology, knowledge transfer included. SGD 15,000/month over 3–6 months. Month-to-month. Up to 50% government co-funded.
Accelerate puts a named, senior AI engineer inside your sprint cadence. They sit in your stand-ups, write in your repos, and ship against your roadmap. You keep the IP, the architecture, and the muscle memory. We bring the AI engineering depth and the FORGE methodology. Most engagements onboard in two weeks and produce production-ready code by month three.
Ten workstreams under one monthly engagement, a senior engineer, a methodology, and a written knowledge-transfer plan from day one.
A named individual, full-time on your programme, with 5+ years in AI engineering. In your stand-ups, your code reviews, your retros, not a far-away agency. A fractional tech lead supports on architecture decisions.
The first three phases of the FORGE methodology applied end-to-end. Phase gates, written deliverables, and a documented decision trail your team can reference long after we leave.
Production-quality code in your repos, your stack, your conventions. Not white-labelled boilerplate. Architecture decision records (ADRs) capture every trade-off.
Backend and frontend built in parallel inside the same sprint. AI-augmented tooling gives 3–5× throughput without sacrificing rigor.
Every Friday: a working demo, a written status note, and a 48-hour-out plan. Your leadership sees the work in progress, no end-of-quarter surprises.
Pair-programming sessions, brown-bag walkthroughs, and written runbooks throughout the engagement. By month four your team is reviewing our PRs, not the other way around.
AI Verify aligned, NIST AI RMF mapped, OWASP LLM Top 10 hardened from sprint one. Evidence pack delivered alongside the code, not bolted on after launch.
We work inside your GitHub, your CI/CD, your ticketing, your infrastructure, not ours. No tool sprawl, no vendor lock-in, no integration debt.
Cancel with 30 days' notice. No long-term lock-in. Most clients renew through month six because the work compounds, but the option is yours every month.
Eligible for IMDA co-funding in Singapore and equivalents across Malaysia (MDEC), Indonesia, the Philippines, and Thailand. We handle the paperwork end-to-end.
Two-week onboarding, then a sprint cadence your team already runs. First production deployment typically lands in month three.
Weeks 1–4. Use-case definition, data audit, success-metric alignment, and a written technical thesis your team and ours both sign off on before code is written.
Weeks 4–8. Reference architecture, governance controls mapped, model and tooling choices documented as ADRs. Your CISO and tech lead review and sign off.
Weeks 8–24. Dual-workflow sprints, weekly demos, knowledge-transfer sessions in cadence. Production deployment with monitoring, written runbooks, and a four-week handover plan.
Accelerate fits teams who have a validated use case and need senior AI engineering depth without a 6-month hire cycle, or the cost of an enterprise engagement.
Series B–D companies with product traction, an engineering team, but no in-house AI engineer to own RAG, agents, or evaluation infrastructure.
Organisations with strong data science and ML modelling capability but a gap on production engineering, Accelerate fills it without disrupting the team.
Teams who validated under Ignite or a sprint, and now need an embedded engineer to take the prototype to a production-ready MVP without rewriting from scratch.
B2B SaaS and fintech teams shipping AI features into existing products, copilots, search, summarisation, alongside their normal product roadmap.
Teams burned by waterfall AI agencies who delivered slides instead of code, Accelerate ships in your repos, in your sprints, in your standards.
Enterprises planning a Tier 3 Deploy engagement who want to de-risk the architecture and the working relationship at lower commitment first.
We had a working RAG demo, a roadmap full of asks, and no senior engineer to own production. EIS embedded one engineer in our sprint inside ten days. By month three we had a multi-tenant RAG service in production, evaluation pipelines our team owned, and two of our engineers who now lead the AI track internally. The engagement paid for itself before the second renewal.
VP of Engineering · B2B SaaS Scale-up · 4-month Accelerate engagement
How an embedded engineer actually works inside your team, what month-to-month means, and how IP and co-funding flow.
30-minute scoping call. We'll size the engagement, name the engineer, confirm co-funding eligibility, and tell you honestly whether Accelerate fits, or whether Ignite or Deploy is the better starting point.