1. Telephony stream
- Audio forked from the contact center platform per call
- Separate channels for agent and caller
- Call ID and queue passed with the stream
- Guardrail: stream starts only after the recording notice plays
AI Agents / Contact Center Agent Assist
GenAI Agent Assist for Healthcare Contact Centers
Member and patient calls stall while agents search five systems and three policy binders for one answer. Agnotic Technologies builds generative AI agent assist that listens with the agent, finds the approved answer and writes the call summary, so the person on the phone stays in charge of every reply.
Agent stays in controlAnswers from approved documentsIdentity checked firstHIPAA-ready
Trusted by global innovators
What is genai agent assist?
GenAI agent assist is software that works beside a human contact center agent during a live call: it transcribes the conversation, suggests answers from approved plan and policy documents, shows member context after identity checks and drafts the after-call summary. Agnotic Technologies builds it for payer and provider contact centers.
It is not a bot that talks to callers. The caller hears a person. The software reads along, so the agent spends less of the call searching and more of it listening.
That difference shapes every design choice below. A suggestion the agent ignores costs nothing. A suggestion the agent reads aloud has to be correct, current and drawn from a document the compliance team approved.
Agent assist or virtual agent
Agent assist or virtual agent: which does your contact center need?
Most contact centers end up with both. The question is which calls each one should handle, and the answer depends on how much judgment the call needs.
| Question | Agent assist | Virtual agent |
|---|---|---|
| Who talks to the caller? | A human agent, with AI suggestions on screen | The AI, by voice or chat, until it hands off |
| Best for | Benefits questions, claim disputes, billing and care questions that need judgment | Status checks, ID card requests, appointment changes and other repeatable tasks |
| What a wrong answer costs | The agent catches it before speaking | The caller hears it, so the scope must stay narrow |
| PHI exposure | Shown to a verified agent after the caller is verified | Disclosed by the system, so verification must be automated |
| How it improves | Agent edits and dismissals show which answers fail | Containment and hand-off reasons show which tasks to add or remove |
For self-service voice and chat on their own, see our healthcare voice AI agents and virtual health assistant pages. This page covers the human side of the call.
Reference architecture
How do you build genai agent assist?
Six stages run on every call. Each one has its own guardrail, because a failure at any stage reaches the caller through the agent's voice.
2. Speech to text
- Streaming transcription with speaker labels
- Custom vocabulary for plan, drug and procedure names
- Partial results for live suggestions, final text for the summary
- Guardrail: member ID and card numbers masked in the transcript
3. Retrieval over approved documents
- Plan documents, benefit grids and call scripts indexed by plan and year
- Only documents with an approved status and a current date
- Every passage carries its source and version
- Guardrail: no answer without a cited passage
4. Member or patient context
- CRM, eligibility, claims or scheduling data read on demand
- Fields limited to what the call reason needs
- Open cases and prior contacts shown as a timeline
- Guardrail: nothing shown until identity verification passes
5. Suggestion panel
- Suggested answer with its cited passage
- Next step from the call script for the detected intent
- Agent can accept, edit or dismiss with one click
- Guardrail: suggestions are text for the agent, never spoken to the caller
6. After-call write-back
- Draft summary, call reason and disposition code
- Agent reviews and edits before saving
- Saved to the CRM case with the transcript reference
- Guardrail: nothing written to the record without the agent's save
Virtual agent hand-off
How does a virtual agent hand a call to a person?
The hand-off is where callers most often repeat themselves. We build it so the agent picks up the call already knowing what happened.
The virtual agent detects it should stop
The caller asks for a person, the intent is outside the virtual agent's scope, confidence drops below the set threshold, or the caller fails identity checks twice.
Context is packaged
Call reason, verified identity status, what the caller already answered and what the virtual agent already told them, in a short structured note.
Routing picks the queue
The contact center platform routes by intent, language and plan, and the context note travels with the call rather than in a separate system.
The agent sees the note first
The suggestion panel opens with the hand-off note, so the agent greets the caller with the reason already known and does not ask for it again.
The hand-off reason is logged
Each reason is counted by intent, so the team can decide which tasks the virtual agent should take on next, and which it should stop attempting.
What does an agent assist build include?
Each capability can ship on its own. Many contact centers start with after-call summaries, because they save time on every call without changing what agents say.
Live transcription
Streaming speech to text with speaker separation, tuned for plan and clinical vocabulary.
Grounded answer suggestions
Answers from approved documents only, each with its cited passage and version.
Verified member context
Eligibility, claims or scheduling details shown after identity checks, limited to the call reason.
After-call summaries
Draft summary, reason and disposition written to the CRM case once the agent saves it.
Virtual agent hand-off
A structured context note that arrives with the call, so callers do not repeat themselves.
Supervisor review queue
Sampled calls, overridden suggestions and summary edits gathered for quality review.
Failure points
Where does agent assist go wrong?
These are the failures we design against from the first sprint. Most are about timing and trust, not the language model.
Challenge
Suggestions arrive after the agent has already answered
Agnotic approach
A latency budget for each stage, partial transcripts for early intent detection, and suggestions dropped if they would arrive too late to help.
Challenge
An answer from last year's plan document
Agnotic approach
Documents are indexed with plan, product and effective dates, and retrieval filters on the caller's plan and the date of the call before ranking.
Challenge
Member details on screen before the caller is verified
Agnotic approach
The context panel is locked until the verification step in the call flow is complete, and the moment it opens is logged with the agent and time.
Challenge
Summaries that agents stop reading
Agnotic approach
Short structured summaries with call reason, actions and follow-ups, and a weekly review of agent edits to see which parts the model gets wrong.
Challenge
Transcription errors on drug and plan names
Agnotic approach
Custom vocabulary from the plan's formulary and product names, and suggestions that show the matched term so the agent can spot a mishearing.
Challenge
Supervisors assume the AI is checking quality
Agnotic approach
Quality review stays with people. The system samples calls for supervisors to review and highlights where the agent overrode a suggestion.
Compliance as engineering
How do you keep PHI safe on a live call?
Agent assist sees more member data per minute than most systems. We treat each control as a product requirement, written into the call flow.
Verification before disclosure
The caller's identity and authority are checked before any member data reaches the agent's screen, and the check is recorded on the call.
Minimum necessary on screen
The context panel shows only the fields the detected call reason needs. A pharmacy question does not open the full claims history.
Recording consent and retention
Recording and transcription start after the notice your legal team approves, and audio, transcripts and summaries each follow your retention schedule.
Audit trail and BAA
Every suggestion shown, accepted or dismissed is logged. Agnotic signs a business associate agreement before any PHI is shared, and model providers are covered too.
Compliance-First Healthcare App Development Services Backed by Global Standards
01
HIPAA
Health Insurance Portability and Accountability Act
Protect PHI with privacy-first architecture, encrypted storage and transmission, strict access controls, and traceable audit logs.
02
GDPR
General Data Protection Regulation
Implement lawful consent flows, data minimization, retention controls, and secure processing for sensitive health data.
03
FHIR
Fast Healthcare Interoperability Resources
Enable standardized health data exchange across apps, care teams, and systems through standards-based FHIR APIs.
04
HL7
Health Level Seven International
Support enterprise-grade interoperability with HL7-based integrations for records, events, and clinical messaging workflows.
05
HITRUST
Health Information Trust Alliance
Align security programs to healthcare-specific control and risk management practices trusted by providers and ecosystem partners.
06
HITECH
Health Information Technology for Economic and Clinical Health Act
Design with breach notification readiness, digital record safeguards, and operational controls that support regulated care programs.
07
SaMD
FDA Software as a Medical Device
Plan software quality, traceability, and documentation pathways for products that may require SaMD review and submission.
08
MDR (EU)
Medical Device Regulation (European Union)
Prepare EU market-ready processes for risk classification, evidence tracking, and lifecycle governance under MDR expectations.
09
SAMHSA
Substance Abuse and Mental Health Services Administration
Apply confidentiality controls and consent-aware sharing models for behavioral and mental health data experiences.
Scope drivers
What drives genai agent assist cost?
We size the work on a scoping call rather than quote a price. These factors move effort the most.
Contact center platform
How audio can be streamed out of your telephony platform, and whether it already offers a real-time media API.
Number of document sets
Each plan, product and year adds documents to approve, index and keep current.
Systems behind the context panel
CRM, eligibility, claims and scheduling each add an integration and a data access review.
Languages
Each language needs its own transcription tuning, document set and quality review.
Hand-off from an existing virtual agent
Passing context from a bot you already run is simpler than building the virtual agent as well.
Startup product or internal build
A startup selling agent assist to many contact centers needs tenant separation from day one.
Who it is for
Which contact centers use agent assist?
The same pipeline, tuned to different calls.
Health plan member services
Benefits, claims status and prior authorization questions answered from plan documents.
Provider service lines
Network, credentialing and payment questions from provider offices calling the plan.
Health system patient access centers
Scheduling, referrals and billing questions with the patient's open orders on screen.
Pharmacy benefit call centers
Formulary, coverage and refill questions with the member's plan rules cited.
Nurse advice lines
Protocol lookup for the nurse, with clinical decisions left entirely to the nurse.
Contact center software startups
Agent assist built into a product sold to payers and providers.
How we work
How does an agent assist engagement work?
Three stages. The first release is agreed and fixed before any code is written.
1.
Scoping call
We pick one queue and one call type, list the documents and systems it needs, and agree how agent acceptance will be measured.
One queue
2.
Fixed-scope first release
Transcription, retrieval and the suggestion panel for that queue, tested on recorded or synthetic calls before a live pilot.
Fixed scope
3.
Scale and support
More queues, languages and the virtual agent hand-off, with document updates and suggestion quality reviewed every month.
Reviewed
Facts and sources
Which rules shape agent assist in healthcare?
Short facts we design the call flow around, each linked to its primary source.
Before a disclosure permitted by the HIPAA Privacy Rule, a covered entity must verify the identity of the person requesting protected health information and that person's authority to have it, when the identity or authority is not already known.
Source: 45 CFR 164.514(h) (eCFR)When using or disclosing protected health information, a covered entity or business associate must make reasonable efforts to limit it to the minimum necessary for the purpose of the use, disclosure or request.
Source: 45 CFR 164.502(b) (eCFR)The HIPAA Security Rule requires procedures to verify that a person or entity seeking access to electronic protected health information is the one claimed.
Source: 45 CFR 164.312(d) (eCFR)Systems that contain or use electronic protected health information must have hardware, software or procedural mechanisms that record and examine activity in them.
Source: 45 CFR 164.312(b) (eCFR)
Frequently Asked Questions
No. Agent assist shows suggestions to the human agent, who decides what to say. If you also want a virtual agent that talks to callers, we build the hand-off between the two so context moves with the call.
Suggestions come only from documents your team has approved for the caller's plan and date, and each one shows its source passage. The agent reads the passage before using it, and dismissed suggestions are reviewed to find gaps in the documents.
Yes. We connect to your contact center platform for audio, your CRM for cases and summaries, and the eligibility, claims or scheduling systems agents already use. The work starts by checking how each system exposes real-time data.
That depends on your telephony platform, the number of document sets and the systems behind the context panel. We fix the scope of a first release for one queue on the scoping call and plan the dates from it.
Yes. A common first release is after-call summaries for one queue, because it saves time on every call without changing what agents tell callers. Live answer suggestions follow once the document set is approved.
Audio, transcripts and summaries are stored in your environment or infrastructure you approve, encrypted, and deleted on the retention schedule your compliance team sets for each one. Masked fields never reach long-term storage.
Our engineers use AI tools for drafts and tests and review every change themselves. Development uses synthetic calls and test documents, and real member audio is only used in a pilot your compliance team has approved under a BAA.