Generative AI Development Services
Senior engineers, assigned to your build
ABM Tech creates generative AI solutions for text, voice, vision, and gaming. Build high-quality original content at scale with production-ready AI.
Scope my generative AI build→Why teams pick ABM Tech
Security built in, not bolted on
Encryption, access control and compliance designed into the architecture from the first sprint — the way our Swedish healthcare consent platform was built.
Working hours that overlap
Singapore-based engineers who keep to your business day, so standups, reviews and decisions happen live rather than overnight.
You interview them first
Named engineers put forward with real profiles. You meet anyone joining your engagement before they start, and nobody below the bar gets proposed.
Productive inside two weeks
Scoping, team assembly and access sorted without a procurement marathon — first commit typically lands in week two.
Reviewed in the open
Our delivery record is published and verifiable on Clutch, DesignRush and The Manifest rather than summarised in a slide.
Engagements that keep going
Most clients extend past the first delivery, which is the only retention signal that actually means anything.
Generative AI Development Services
Generative AI has moved from experimental to mission-critical in a span of two years — but most enterprise initiatives stall at the proof-of-concept stage because the gap between a compelling demo and a production-grade, cost-controlled system is wider than marketing materials suggest. ABM Tech has been building ML-backed products since 2016, long before the LLM wave, which means our engineers understand both the statistics underneath generative models and the software engineering discipline needed to ship them reliably.
Our generative AI engagements typically span the full delivery stack: prompt architecture, retrieval augmentation, model selection and cost modeling, guardrails and output validation, API gateway design, and the observability layer that tells you when a model starts hallucinating in ways your evals missed. We do not hand you a notebook and call it done.
U.S. timezone alignment matters here more than in traditional software because generative AI work is inherently iterative — a design decision made at 10 AM needs a fast feedback loop, not a 12-hour async lag. Our senior Singapore engineers work your hours, so prototyping cycles that typically stretch across two weeks compress into days.
The challenge
Most organizations have a business case for generative AI but lack the internal infrastructure to deploy it safely: no evaluation harness, no latency budget analysis, no cost ceiling guardrails, and no clear ownership of model updates when OpenAI or Anthropic ships a breaking change. Proofs of concept that look great in a demo routinely degrade in production under real traffic and real user inputs.
Our approach
ABM Tech architects generative AI systems with production constraints as the starting point, not an afterthought. We define evaluation criteria and failure modes before writing a single prompt, select models against latency and cost targets rather than benchmark leaderboards, and build streaming API layers and fallback chains so you are never dependent on a single provider's availability.
The outcome
Engagements conclude with a deployed, monitored generative AI feature — not a prototype — complete with an eval suite, a cost dashboard, and documented handoff so your team can own it forward. Teams that move from prototype to production with the right infrastructure in place commonly see meaningful reductions in manual review burden and measurable deflection of routine support requests — the scope of those gains depends on how the system is scoped and adopted.
Get a production readiness assessment and cost model within 5 business days.
Case Studies
Built, launched, and still running.
Selected engagements
Browse all cases→
AI & Data Science
Sentiment Analysis & Trend Prediction
Multilingual NLP pipeline reading sentiment, sarcasm and emerging trends across global social channels.
Consent Management System Integration
Healthcare · Sweden
Digital patient consent platform for Sweden's healthcare sector — BankID-integrated, cutting consent processing time by 86%.
Online Consultation Platform Integration
Healthcare · Telehealth
HIPAA-compliant telehealth platform pairing people with qualified therapists — booking, secure video sessions and progress tracking.
Shopping Platform Creation
E-commerce
Deal and coupon aggregation platform with algorithmic coupon stacking across leading U.S. retailers.
Integrating APIs with the ServiceNow Platform
Enterprise Integration
REST API integration into ServiceNow that replaced error-prone manual workflows with automated ones.
The metrics that follow from shipping with senior engineers
4.9 / 5
Average client rating across platforms
93%
Net Promoter Score
Long-run
Client retention rate
Secure
Type II certified
Pick the engagement that fits
Four ways to work with us — from surgical staff augmentation to fully managed delivery. All models share the same senior-first talent bench.
Dedicated Teams
Full-time engineers embedded in your team for long-running engagements.
Explore Dedicated Teams↗Staff Augmentation
Add senior specialists to an existing team — vetted, onboarded, and up to speed in weeks.
Explore Staff Augmentation↗Project Delivery
Managed fixed-scope projects with a committed timeline and deliverables.
Explore Project Delivery↗Why ABM Tech
What keeps clients past the first delivery.
What clients tell us made the difference, usually somewhere around the second sprint.
Production-First Architecture
We design for throughput, latency ceilings, and cost per request from day one — not retrofitted once the demo starts breaking under load.
Evaluation-Driven Development
Every generative feature ships with a regression eval suite so you know immediately when a model update changes output quality or introduces new failure modes.
Multi-Provider Resilience
We build provider-agnostic abstraction layers with fallback chains across OpenAI, Anthropic, Google, and open-weight models so uptime is never held hostage to a single vendor.
Guardrails and Output Validation
Structured output schemas, semantic content filters, and PII scrubbers sit between the model and your users — not as an optional layer but as a core delivery requirement.
Observability and Cost Control
Token usage dashboards, latency p95 tracking, and automated budget alerts mean finance and engineering share a single source of truth on what generative AI actually costs.
Senior Engineers, Your Hours
Our Singapore team operates in U.S. time zones, compressing the feedback loops that make iterative AI work go fast rather than stretching experiments across 48-hour async cycles.
Why Teams Choose Us
Security built in, not bolted on
Encryption, access control and compliance designed into the architecture from the first sprint — the way our Swedish healthcare consent platform was built.
Working hours that overlap
Singapore-based engineers who keep to your business day, so standups, reviews and decisions happen live rather than overnight.
Top Rated
Near-perfect satisfaction scores across Clutch, DesignRush, and Manifest.
How we work
Scoping call to production release.
Every engagement is staffed with named people whose only assignment is your build. No shared allocation, no roster of contractors matched to a brief.
Week zero
We start by arguing with the brief.
A working session on the problem, not a requirements hand-off.
The first conversation is technical. We go through the system you have, the constraints you are stuck with, and what would count as this having worked — and we push back where the brief and the goal disagree. The people in the room are the ones who would build it, because nobody else can tell you the architecture will not hold.
A walk through your existing stack, data and integration constraints
Run by the engineers who would staff the build, not an account manager
You leave with a scope, a team shape and the risks named out loud
FAQ
The questions that come up before you start.
Engagement models, pricing, security, and how we staff a project — answered straight, with the detail you would ask for on a first call anyway.
For a well-scoped feature — say, a document Q&A assistant or an automated email-drafting tool — expect 6 to 10 weeks from kick-off to production deployment. That timeline covers prompt architecture, retrieval pipeline if needed, API integration, an eval harness, and a staging-to-production cutover. More complex multi-agent workflows or fine-tuned model integrations add 4 to 8 weeks depending on data readiness.
Keep exploring