We handle the full spectrum of AI data operations — from annotation and evaluation to building the software systems that run on top of that data. One team covering both sides.
Get in Touch →We generate, annotate, validate, and evaluate the training data that AI systems depend on. Schema-compliant delivery with documented fix cycles — not crowdsourced annotation.
We annotate multi-turn agentic conversation trajectories for AI safety evaluation — tool call labelling, PII entity identification, and cumulative scoring across turns.
We review, rank, and correct AI outputs — building the preference datasets that make models safer and better aligned with human values.
We prepare SFT datasets from scratch or clean and validate existing datasets — following your format spec and quality rubric precisely.
We generate synthetic prompt-response pairs for LLM training and validate them before they enter your pipeline — catching fabrication, schema errors, and SOP violations systematically.
We provide structured human evaluation of LLM outputs — scoring responses against defined rubrics, running model comparisons, and executing benchmark tasks.
We provide structured human review at every stage where automation alone is not sufficient — from pre-training data validation to live output monitoring.
We review and validate existing data, outputs, and workflows against defined standards — prompt QA, schema validation, SOP compliance, tool-calling validation, and red teaming.
We collect and annotate data for AI training — gathering voice recordings, images, and text data, then labelling it for machine learning pipelines.
We provide structured review of AI-generated outputs for quality, safety, bias, and policy compliance — systematically, not just spot-check.
We build RAG pipelines, agentic systems, LLM fine-tuning pipelines, and GPU model serving infrastructure — shipped and running in production.
Retrieval-Augmented Generation systems built for accuracy and reliability — multi-source retrieval, reranked, and monitored.
Multi-agent systems with stateful reasoning, tool use, and autonomous task execution using LangGraph and custom state machines.
We build and run fine-tuning pipelines for domain adaptation and task specialization using LoRA/PEFT — full lifecycle from dataset generation to evaluation.
GPU-optimized model serving for production workloads — multiple large models concurrently with efficient memory allocation and full monitoring.
Custom conversational agents built for production — with memory, routing, fallback handling, and full observability. Not a thin API wrapper.
AI-powered automation flows connecting your systems — n8n, CRM integrations, webhook pipelines, document intelligence, and LLM-powered generation.
We build web applications, mobile apps, and cloud infrastructure. Dedicated engineering teams or fixed-scope projects.
We build web applications from the ground up — from simple sites to complex platforms with authentication, data pipelines, and real-time features.
We build cross-platform mobile apps using Flutter and React Native — one codebase, both iOS and Android.
We design, build, and manage cloud infrastructure on AWS, GCP, and Azure — from your first deployment pipeline to a scalable production environment.
We build automated test suites that catch issues before your users do — integrated into your CI/CD pipeline so every deployment is validated.
Agentic annotation, RLHF, SFT data, synthetic prompt generation and QA, LLM evaluation, prompt QA validation, schema validation, and HITL operations for clients building AI and LLM systems.
Production RAG pipelines, multi-agent systems built with LangGraph, LLM fine-tuning pipelines, GPU model serving with vLLM and SGLang, document intelligence platforms — shipped and maintained in production.
Full-stack web applications including billing systems, job boards, and data processing tools. Mobile apps. Cloud infrastructure. AI/ML engineering integrated into client products.