AI Solutions That Work Inside Your Product, Not Just a Demo
Nexlantic builds AI features and machine learning systems that run in production: assistants and copilots on OpenAI and Claude models, document processing, forecasting, computer vision and workflow automation, with the evaluation and guardrails to trust them.
- ML Model Development
- NLP & Chatbots
- Predictive Analytics
- AI Integration
AI Solutions that fits how your business runs
Most AI projects stall between a promising demo and a feature customers can rely on. The gap is engineering: retrieval over your own data, prompt and model evaluation, cost and latency budgets, fallbacks when a model is wrong, and monitoring once real users arrive. We treat AI as a product capability with those pieces built in, so what you launch keeps working after the novelty wears off.
For language tasks we integrate large language models from OpenAI and Anthropic's Claude, grounding them in your documents and systems with retrieval-augmented generation and tool use. For prediction and classification we train conventional machine learning models in Python with TensorFlow and scikit-learn where they beat a general model on cost or accuracy. Computer vision, speech and document extraction follow the same rule: use the simplest approach that meets the measured target.
Data privacy shapes every design. Sensitive data can stay inside your cloud account, prompts and outputs are logged for audit, and access follows the same roles as the rest of your platform. Our engineers in New York and Islamabad work alongside your domain experts so the system encodes how your business actually operates.
Why teams choose Nexlantic for AI solutions
Grounded in your data
Retrieval pipelines over your documents, databases and APIs give assistants accurate, cited answers instead of confident guesses.
Measured, not assumed
Evaluation sets, regression tests and human review loops show how a model performs before and after every change.
Automation with guardrails
Agents and workflows act within defined tools and limits, with approvals and audit logs where decisions matter.
Cost and latency in budget
Model routing, caching and right-sized models keep response times and per-request costs within targets as usage grows.
What's included
Everything a AI solutions engagement covers, from the first workshop to handover.
- AI opportunity assessment and use-case prioritisation
- Proof of concept with success metrics
- LLM integration with OpenAI or Claude
- Retrieval-augmented generation over your data
- Custom model training and fine-tuning
- Evaluation harness and quality monitoring
- Agent and workflow automation
- Privacy, access and audit controls
Our AI solutions process
Four focused stages, each with a clear deliverable and a decision point for your team.
- 01
Find the right problem
We review workflows and data to pick use cases where AI changes an outcome, and define how success will be measured.
- 02
Prove it on real data
A short proof of concept runs against your actual documents or records with an evaluation set, so decisions rest on evidence.
- 03
Productionise
The winning approach is rebuilt as a service with retrieval, guardrails, monitoring, cost controls and integration into your product.
- 04
Improve continuously
Usage data and feedback flow back into prompts, models and evaluation sets so quality rises after launch instead of drifting.
Technologies we use
The tools we reach for on AI solutions work, chosen per project rather than by habit.
- OpenAI
- Claude AI
- Python
- TensorFlow
- scikit-learn
- LangChain
- PostgreSQL
- pgvector
- Node.js
- TypeScript
- AWS
- Azure
AI Solutions for your sector
Healthcare software
HIPAA-compliant platforms, telehealth solutions, and patient engagement tools that improve care delivery.
Learn moreFinance software
Secure fintech applications, payment processing, and regulatory-compliant financial platforms.
Learn moreCRM Systems software
Custom CRM platforms, sales pipelines, customer portals and integrations with Salesforce, HubSpot and Dynamics 365.
Learn moreRetail software
E-commerce platforms, inventory management, and omnichannel experiences that drive sales.
Learn more
Often paired with
Data Analytics
Turn enterprise data into insight with modern analytics pipelines, visualization, and decision intelligence.
Learn moreWeb Development
Custom web applications built with React, Next.js, and modern frameworks. Scalable, secure, and optimized for performance.
Learn moreCloud Solutions
Cloud architecture, migration, and DevOps on AWS, Azure, and GCP. Infrastructure that scales with your business.
Learn more
AI Solutions questions, answered
Still unsure? Book a 30-minute call and we will walk through your situation.
Customer and employee assistants, document understanding and extraction, search over internal knowledge, forecasting and recommendation models, computer vision for inspection and intake, and automated workflows that use language models with defined tools. Each is built as a production feature with evaluation and monitoring.
All three, depending on the task. We evaluate candidate models on your data for accuracy, latency and cost, and often route between them. Where data residency matters we can run models inside your own cloud account.
By grounding responses in retrieved sources, constraining outputs with schemas, adding verification steps, and testing against an evaluation set before each release. Where errors carry real consequences we add human approval and keep an audit trail.
No. We use API agreements and configurations that exclude your data from provider training, keep sensitive content in your environment where required, and document the data flow so your security and legal teams can review it.
A focused proof of concept with a defined evaluation set is usually a matter of weeks. It produces measured results and a clear recommendation on whether and how to build the production version.
Ready to start your AI solutions project?
Tell us what you are building. We reply within one business day with next steps and a proposed team.