We embed AI into your products, workflows, and systems — LLMs, autonomous agents, and intelligent automation built for reliable, production-grade deployment that scales without additional headcount.
Most businesses know they need AI but cannot find a safe, practical path forward. Off-the-shelf AI tools do not fit real workflows. Custom AI development feels expensive and risky. The result is paralysis — an organisation that knows it is falling behind but cannot act. Proof-of-concept projects run for months without reaching production. AI becomes a demo, not a capability.
We do not sell AI as a product — we embed intelligence into the operational layer of your business. We start with your actual workflows, your actual data, and your actual constraints. We identify where AI creates genuine leverage, build integrations that work with what you already have, and deploy systems your team can trust and measure.
Connect OpenAI, Anthropic, Google, and open-source models to your business data and workflows. Prompt engineering, context management, and output reliability at production scale.
Build agents that plan, act, and complete multi-step business tasks without human supervision — sales agents, ops agents, support agents, finance agents.
Retrieval-augmented generation over your internal documents, policies, and data. Your business knowledge made queryable and reliable.
Extract structured data from unstructured documents — invoices, contracts, reports, forms — with 95%+ accuracy and full audit trails.
Train and fine-tune models on your specific data for prediction, classification, and anomaly detection tasks where off-the-shelf models don't fit.
Model deployment pipelines, performance monitoring, drift detection, and retraining automation — so your AI systems improve over time, not degrade.
Map workflows, quantify manual effort, identify highest-leverage AI opportunities. Prioritise ruthlessly — not everything should be automated.
Working prototype on a contained version of the problem in 2–3 weeks. You see something real before committing to a full build.
Full development — model selection, prompt engineering or fine-tuning, API build, system integrations, edge case testing.
Deployed to your environment with confidence thresholds, human escalation paths, full audit trails, and performance monitoring.
AI systems improve with use. We analyse performance data, retrain models, expand capabilities, and respond to real-world feedback.
A B2B software company had SDRs spending 40% of their time manually qualifying inbound leads — reading submissions, researching companies, writing first emails. We built an AI agent that does all of this autonomously within 4 minutes of form submission.
Lead response time from 6 hours to under 5 minutes. SDR team reclaimed 3 full days per week. Qualified pipeline increased 34% in 90 days.
A logistics company processing 400+ vendor invoices monthly had 3 people spending 2 weeks on it each month. We built a document intelligence system that handles 90% of invoices autonomously, flags exceptions, and posts directly to their ERP.
Processing time from 2 weeks to 2 days. Error rate from 8% to under 0.5%. Finance team redeployed to strategic work.
A SaaS company with 800+ tickets per month — 70% being the same 15 question types. We trained an LLM on their knowledge base to handle tier-1 tickets autonomously and escalate complex cases with full context.
First-contact resolution from 42% to 71%. Average response time from 4 hours to 3 minutes.
A focused, well-scoped AI integration takes 6–12 weeks from kickoff to production. We always start with a 2–3 week proof of concept before committing to a full build.
No — but we conduct a data audit in the first week to understand what you have and what gaps exist. For some use cases we can start immediately; for others we may need to build data collection first.
We are model-agnostic — OpenAI, Anthropic, Google, and open-source models (Llama, Mistral) depending on cost, performance, data privacy, and deployment constraints.
Every system we build has configurable confidence thresholds, human-in-the-loop escalation paths, and full audit trails. We monitor error rates post-launch and retrain or adjust as needed.
Drop us a line and a real person from Stack18 will get back to you within one business day.
Reaching out from: Artificial Intelligence.