Supercharge operations with intelligent AI agents that act, learn, and execute.
DGTLtechhub builds production-ready AI agents—combining large language models, secure data pipelines, and enterprise orchestration—to automate decision workflows, accelerate research, and reduce manual toil. Every agent is designed to integrate into your stack, scaled for reliability, and hardened for compliance.
AI agents that research, decide and execute — built for enterprise scale
We design agents that do more than reply: they understand your domain, reference your data (securely), orchestrate actions across systems, and continuously improve. From rapid pilots to production rollouts, we emphasize measurable ROI, reproducible MLOps, and governance-ready deployments.
Agent Consulting & Strategy
Rapid assessments to find high-impact automation opportunities, clear success metrics and low-risk pilot roadmaps so teams can validate value quickly.
Custom AI Agent Development
Domain-adapted agents built with RAG, fine-tuning, state management, and robust test coverage — engineered for predictable, auditable behavior.
Agent Integration & Orchestration
Secure connectors, event-driven hooks and containerized runtimes that let agents interoperate with CRMs, databases, ERPs and internal tools with low latency.
Monitoring, Safety & Support
Continuous monitoring, drift detection, human-in-the-loop controls, and SLAs — we keep agents safe and effective as load grows and models evolve.
Conversational Agents
Context-aware assistants that manage multi-turn flows, escalate seamlessly to humans, and keep conversation state intact.
Generative Agents
Domain-aware content and report generation with controls for brand voice and factual grounding.
Autonomous Task Agents
Planners that execute multi-step tasks, call APIs, reconcile results and self-correct with retry logic and observability.
Orchestration Agents
Coordinator agents that manage pipelines, approvals, and multi-agent workflows end-to-end.
Technology & Platform
Reusable agent patterns, reproducible pipelines, and standardized integrations that reduce drift and maintenance cost.
IT, Security & Compliance
Designed for governance: audit trails, role-based data access, encryption, and automated policy checks.
Operations
Automated routing, exception handling and process optimization to reduce manual effort and cycle time.
Customer Experience
Faster answers, consistent responses and personalized journeys that improve satisfaction and retention.
Finance
Fraud detection assistants, automated underwriting helpers, and personalized insights at scale.
Retail
Demand forecasting agents, merchandising automation, and AI-assisted product discovery.
Healthcare
Clinical summarization, triage assistance and secure clinical workflows to accelerate clinician decisions.
Logistics & Supply Chain
Smart routing, ETA prediction, and exception handling agents to reduce cost and improve reliability.
Insurance
Claims triage, document extraction and risk scoring agents that improve processing speed and consistency.
Validate use-cases, quantify ROI, and map data and system touchpoints for a clear, low-risk pilot plan.
Define architecture, retrieval strategy, privacy model and prompt governance for robust behavior.
Implement agents, integrate vector stores, create APIs and CI/CD with strong test coverage.
Functional, safety, and human-in-loop evaluations to ensure reliability and reduce risk of misbehavior.
Phased rollouts, canary releases, and production monitoring with alerting around key signals.
Ongoing tuning of prompts, retraining cadences, and pipeline improvements to keep agents effective as data changes.
LLMs & Frameworks
OpenAI, Anthropic, Hugging Face, LangChain — chosen per privacy, cost and performance needs.
MLOps & Orchestration
Kubeflow, MLflow, Airflow and robust CI/CD keep models reproducible and pipelines observable.
Cloud & Infra
Multi-cloud deployments (AWS, Azure, GCP) with autoscaling, secure networking and low-latency inference options.
Vector Stores & Data
Pinecone, FAISS, Qdrant — combined with secure encryption and careful data governance.
Take the Next Step Toward Real Outcomes
Share your idea or request a quote — our team will respond within one business day.
Typical timelines are 6–8 weeks for many useful agents (pilot → production). Complexity, number of integrations, regulatory constraints, and need for fine-tuning can extend timelines. We always run a short discovery to give a precise estimate.
Cost depends on integration count, workflow complexity, whether models are hosted or self-hosted, fine-tuning needs, data privacy and SLA requirements. We provide phased options so you can start small and expand.
We combine retrieval-augmented generation (RAG), citation & grounding strategies, output validators, and monitoring. In high-risk flows we add deterministic checks and human-in-the-loop gates before critical actions.
Yes — we deploy agents to AWS, GCP, Azure, hybrid cloud, or on-premise environments with encryption, audit logs and RBAC to meet compliance needs.