AI & Machine Learning
Beyond demos. AI that ships to production.
We turn generative AI, RAG, agents, computer vision and predictive ML from boardroom slides into working products. Every engagement ships measurable business impact, not a Jupyter notebook.
What you walk away with.
- AI roadmap aligned to revenue, retention or cost lines
- Production-ready LLM apps with guardrails, evals and audit logs
- Domain-tuned retrieval systems on your private data
- AI agents that take real actions across your tools
- Computer-vision and document-AI pipelines wired into ops
- MLOps stack you can hand to your team on day 31
A typical AI/ML deliverable in production.
What we deliver.
The tools, picked deliberately.
We do not chase trends. We pick the best tool for your team, scale and constraints, and we explain why.
The four phases of every engagement.
Discovery & ROI mapping
We audit your data, workflows and KPIs, then pinpoint the 1–3 AI bets with the strongest ROI signal.
Rapid prototype
A working prototype in 2–4 weeks against your real data, with evals, not vibes.
Production hardening
Guardrails, observability, cost controls, security review, and CI/CD for prompts and models.
Launch & continuous evals
Ship to users, instrument outcomes, run A/B tests and retrain on real signal.
Where this lands well.
Sales copilot
Lead qualification, deal coaching, and pipeline forecasting on top of your CRM.
Support automation
RAG-grounded answers, ticket triage, and AI agents that resolve tier-1 cases.
Document AI
KYC, invoices, contracts and forms parsed into structured data at 99%+ accuracy.
Predictive maintenance
IoT + ML to flag equipment failure days before it happens.
Demand forecasting
ML models tuned on your historical data to align inventory, production and procurement.
Fraud & anomaly detection
Real-time models that flag suspicious transactions or operational outliers before they escalate.
Pair this service with Tilarq.
Many engagements get a head start by leveraging our own products: Soliq as the intelligence engine underneath, with Tilarq CRM on top where relevant.
Questions about AI & Machine Learning.
Both. We pick the model that fits your accuracy, latency, cost and data-residency needs, and we keep the architecture model-agnostic so you can swap providers without rebuilding the app.
Every production system we ship includes retrieval grounding, structured outputs, eval harnesses, PII redaction, prompt-injection defenses and full audit logs. Sensitive workloads run inside your VPC or on-prem.
Yes. We fine-tune open and closed models (LoRA, QLoRA, full fine-tunes) and run private deployments on AWS Bedrock, Azure AI, GCP Vertex, or your own GPU cluster.
Ready when you are
Let's build something exceptional.
Tell us about your business, your stack, and the problem you are trying to solve. We respond with a clear next step usually a 30-minute discovery call, no fluff.