75+
Engineers
Kodertal delivers production-ready AI solutions, from strategy to scale. We design, build, and integrate AI agents, LLMs, chatbots, and automation that fit your workflow, ship faster, and drive measurable business outcomes globally.
AI & LLM Development Services for
Healthcare
We help healthcare teams improve patient care, reduce admin burden, and support faster clinical decisions with secure AI.
75+
Specialists
HIPAA-Ready
Delivery
99.9%
Uptime Targets
10+
Projects Delivered
75+
Specialists
HIPAA-Ready
Delivery
99.9%
Uptime Targets
10+
Projects Delivered
Patient history, labs, imaging, and notes often live in separate systems, so clinicians hunt for context. We see teams spending precious minutes switching tabs, exporting reports, or calling other departments. That fragmentation slows care and increases risk of missed details. Our goal is to unify data access so decisions happen faster and with more confidence at the point of care.
When data stays siloed, AI cannot learn the full story, and predictions become noisy. We help map sources, standardize identifiers, and build retrieval layers that pull the right records safely. Our integrations respect role-based access and PHI boundaries, while keeping latency low for busy teams. The result is cleaner inputs and more reliable AI outputs across workflows every day.
We build decision support that summarizes patient context, flags gaps, and suggests next steps, grounded in records and guidelines, with audit logs and human approval.
We develop risk models that predict readmissions, deterioration, or missed follow-ups using your historical signals, then trigger alerts and workflows with thresholds you can tune.
We deliver imaging AI that assists with detection, triage, and prioritization for radiology and clinical teams, plus quality checks, explainability, and monitoring for drift.
We create assistants that help staff and patients navigate scheduling, instructions, and FAQs, integrated with your systems and designed to protect PHI through safe access controls.
We build chatbots that handle intake, reminders, and common questions, improving response speed while escalating complex cases to humans with full conversation context and routing.
We automate documentation checks, coding support, and claim workflows, reducing denials and rework by extracting structured data and validating it against payer and policy rules.
We connect tasks across EHR, ticketing, and internal tools to remove manual handoffs, using event-driven automation, approvals, and logs so operations stay predictable.
We build monitoring that analyzes device and symptom streams, detects anomalies early, and routes alerts to care teams with configurable thresholds and clear, auditable context.
We convert clinician voice into structured EHR notes, capturing key fields, codes, and context with review-first safeguards.
We generate concise chart summaries from labs, notes, and history, helping clinicians scan context faster and avoid omissions.
We triage prior auth requests by extracting requirements, checking documentation gaps, and routing approvals faster with traceable reasoning.
We predict no-show risk using scheduling signals, then trigger reminders and rescheduling workflows to protect revenue and continuity.
We match patients to trials by extracting eligibility criteria and comparing records, then generating evidence-backed recommendations for review.
We score discharge risk using clinical and social signals, then recommend follow-ups and flags for care coordination teams.
We segment populations by risk and needs, enabling targeted outreach programs, better resource planning, and measurable intervention impact.
We detect suspicious billing patterns using anomaly signals and explainable flags, helping teams investigate faster and reduce losses.
We add LLM assistance to portals for FAQs, instructions, and status checks, reducing call volume with safe escalation.
75+
Engineers
400+
Projects Deployed
27+
Industries Worked In
2
Development Facilities
10+
Years of Experience
350+
Happy Customers
24/7
Support Availability
95%
Client Retention
We design around clinical realities, not generic templates. Our solutions respect workflows, approvals, and patient safety, so teams adopt faster and rely on outputs during real care delivery.
We build LLM features that stay grounded, accurate, and predictable in production. Our team designs prompts, retrieval, tools, and evaluations so assistants support decisions instead of creating noise.
We engineer privacy-first systems with role-based access, encryption, and audit logs. Our approach supports HIPAA-ready delivery while keeping integrations practical, monitored, and safe for regulated environments.
We build secure pipelines that clean, validate, and route data with least-privilege controls. Our logging and governance reduce risk while improving data quality for reliable model performance.
We integrate AI into EHR-adjacent workflows using APIs, middleware, and phased rollouts. Our approach avoids disruption, keeps the EHR as the system of record, and stays auditable.
We define KPIs early—time saved, error reduction, response speed, and adoption—then instrument dashboards to track impact. Our optimization work improves results quarter over quarter.
We keep delivery predictable with clear scope, milestones, and weekly demos. You see progress, risks, and decisions in real time, with documentation that supports handoff and governance.
We stay accountable after launch with monitoring, tuning, and support. As policies, data, and workflows change, we keep your AI reliable, cost-aware, and continuously improving.
We shape roadmaps in 2–4 weeks, prioritize use cases, and align teams, data, and infrastructure together.
Our embedded squad scales with you, delivering weekly demos and supporting 10x growth safely, end-to-end.
We own delivery from discovery to launch in 8–16 weeks, integrating UX, backend, data, and APIs.
We monitor and optimize continuously, targeting 99.9% uptime, lower latency, and predictable costs after launch.
We design privacy-first systems with encryption, role-based access, audit logs, and least-privilege permissions. We separate environments, control data retention, and document data flows. When third-party models are involved, we apply strict routing rules and safe fallbacks to reduce exposure risk.
Yes, we integrate through available APIs, middleware, and phased rollouts that protect uptime. We keep the EHR as the system of record and build AI services around it. We add logging, rate limits, approvals, and reversibility so workflows stay stable.
We typically start with a 2–4 week kickoff to define use cases, KPIs, data readiness, and an implementation plan. Early pilots can show measurable time savings quickly, then we expand scope based on adoption and performance metrics. Weekly demos keep momentum.
Yes, we stay accountable after launch with monitoring, tuning, and ongoing support. We track accuracy, latency, cost, and drift, then improve prompts, retrieval, and workflows. You get a clear optimization backlog, regular updates, and reliability practices aligned to your needs.
We design privacy-first systems with encryption, role-based access, audit logs, and least-privilege permissions. We separate environments, control data retention, and document data flows. When third-party models are involved, we apply strict routing rules and safe fallbacks to reduce exposure risk.
