Empty — First visit, Communications, End of care

First visit: nothing — Sensi is the only adjacent tool, and it requires hardware Communications: WellSky Family Room (exists but unused), ElliQ (adjacent, not purpose-built) End of care: nothing — Sensi Solo Care is the only tool approaching this moment

Sparse — Matching, Performance mgmt

Matching: WellSky CareFinder, AxisCare Intelligence, CareQB Performance: Activated Insights, Sensi.AI (emerging)

Moderate — Intake, Assessment, Care plans, Retention

Intake: AxisCare CRM module, WellSky CRM, HubSpot Assessment: WellSky SkySense, CareSwitch Looper Care plans: AxisCare, WellSky, AlayaCare Retention: Activated Insights, Zingage, WellSky TeamEngage

Crowded — Scheduling, EVV/Compliance, Billing/Payroll, Hiring

Scheduling: WellSky, AxisCare, Phoebe EVV/Compliance: HHAeXchange, Sandata Billing/Payroll: WellSky, HHAeXchange, Waystar Hiring: Indeed, Hireology, Apploi

Getting there → Zingage overview Kare Zingage Perform uses reinforcement learning from real labor data to generate retention alerts for at-risk caregivers before they disengage rather than after. Kare builds a rated track record for caregivers across agencies — reliability and fit signals that accumulate over time rather than disappearing when someone changes employers. Caregivers build a track record; agencies can favorite caregivers they've worked well with, giving them priority on future shifts. Neither has cracked the core problem — no system yet captures why a specific caregiver works with a specific client, or carries that knowledge across agency boundaries. But the direction is right: making caregiver context something that persists rather than something that evaporates.

Competitor insight: WellSky's TeamEngage dashboard tracks 96% adoption, 4% turnover, $23,451 in points redeemed. Documented results are real: Griswold reported a 13% turnover reduction in 7 months. But the metrics being tracked are shift acceptance, punctuality, and hours worked — behavioral compliance, not relationship quality. The system flags a turnover risk score when engagement patterns decline, but by design it flags after disengagement has already started. A caregiver burning out from a bad client match, absorbing extra shifts she wasn't trained for, and feeling surveilled rather than supported will show up in these numbers late. TeamEngage treats the symptom. It has no mechanism to address the match that caused the burnout in the first place.

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3d247417394_0_0#slide=id.g3d247417394_0_0

it deostn translate across workplaces either

Getting there → Screenshot: p.43 — Hireology/Apploi/myCNAjobs myCNAjobs produces approximately 15% lower turnover than Indeed because specialist channel framing attracts candidates with more relevant intent — people who searched specifically for home care work rather than responding to a generic job posting. Hireology standardizes the recruiting process across franchise locations, reducing variability in hiring decisions and creating a consistent decision environment. Neither tool connects hire-source data to 90-day retention outcomes — agencies still know who they hired, not which hires stay. But the channel quality difference is measurable, the data exists, and the feedback loop needed to act on it is the missing piece.

Competitor insight: Indeed is the dominant hiring channel for home care — cited as the #1 recruitment source by 39% of providers — and the retention math explains why hiring never stops. Median turnover for Indeed hires is 88%. Acquisition cost is $561 per hire versus $167 for word-of-mouth. Only 25% of Indeed hires stay longer than two years. Agencies sourcing exclusively through Indeed spend approximately $60,000 more per 100 hires than agencies using specialist channels once churn costs are factored in. The market has this data — Activated Insights publishes it annually — and keeps spending on Indeed anyway. The behavioral mechanism is present bias: high applicant volume feels like progress, and the $4,000 cost of a lost caregiver arrives 90 days later, attributed to retention rather than to the hiring decision that set it in motion.

one solution to this is checking regularly and then learning from how often people actually can follow through- i.e. use phoebe for coverage and start to track when people are avialable.

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3ca731bc964_0_1099#slide=id.g3ca731bc964_0_1099

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3ce32572ca7_0_10#slide=id.g3ce32572ca7_0_10

Kare builds rated track records for caregivers across real placements — both sides rate each other after each shift, reliability scores accumulate, and agencies can favorite caregivers they've worked well with. It's the first model that treats caregiver quality as something earned through actual work rather than declared on intake paperwork. The gap: ratings capture reliability and basic performance. They don't capture the nuanced fit intelligence Holly holds — which caregiver has the patience for an anxious client, the energy for a mobile one, or the flexibility to cover when custody schedules shift. The track record is getting structured. The judgment underneath it is still only in Holly's head.

Competitor insight: WellSky's CareFinder returns a filtered list of caregivers organized by skills, certifications, availability, and client-specific attributes — pets, live-in, car, three levels of clinical competency. It is a thorough constraint filter and it works for what it was designed to do

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3cc0d0ff19c_0_7#slide=id.g3cc0d0ff19c_0_7

Getting there → Screenshot: p.34 — Scheduling & Matching AI category slide A new category of AI matching tools — CareQB, CareMatch, AxisCare Intelligence — is attempting to move beyond hard constraints toward soft-fit recommendations. AxisCare Intelligence uses AWS Bedrock to surface ranked caregiver suggestions. The gap: these tools are only as good as the data already in the ERP, and soft fit — personality, communication style, whether a caregiver will stay when a situation gets hard — has never been entered into the ERP in the first place. The tools are smarter. The underlying data is the same.

even new AI tools that fill shifts and find matches are overweighting things like availability, whcih shift. Like zingage.

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3ca731bc964_0_1148#slide=id.g3ca731bc964_0_1148

Casey finds best-fit caregivers, considers compliance and overtime, and starts outreach.

: Encodes complex constraints; supports parallel outreach but doesnt know real avialability or soft fit

supported by the fact that care giver matching for wellsky looks like this

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3cc0d0ff19c_0_7#slide=id.g3cc0d0ff19c_0_7

How it works Coordinator enters required hours and dates→ CareFinder returns caregivers filtered by skills, certifications, availability, and client-specific attributes (pets, live-in, car)

What It Misses Personality · communication style · emotional needs Physical strength fit ("Betty's too slight") Rapport history · age compatibility Whether a caregiver will stay when needed

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3ccfe8791cf_0_38#slide=id.g3ccfe8791cf_0_38

Competitor insight: AxisCare's Notes tab is a Permanent Priority Notes field, timestamped staff notes, a call log. It is entirely dependent on a coordinator remembering to write something down after a phone call. Whether the family sounded anxious, whether the client seemed more withdrawn than usual, whether a caregiver mentioned something felt off — none of that has a field. It exists if someone typed it. The call log records that a call happened. It doesn't record what the family's concern level is trending toward. What agencies actually track is operational: scheduled visits, hours, tasks. What matters to families is softer: is the caregiver a good fit, is my parent comfortable, is something changing? Those signals live in phone calls and coordinator intuition and don't make it into the system.

Some ai tools are moving in the right direction for monitoring - https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3cdaa87a7a6_0_0#slide=id.g3cdaa87a7a6_0_0 Getting there → Sensi is the only tool in the landscape attempting to capture these signals directly. Its positive interaction log detects a moment in the living room — a caregiver encouraging a client through her exercises — timestamps it, transcribes it, and surfaces it to coordinators who can comment and tag each other on the thread. One coordinator notes: "we've finally found a good caregiver pairing for Alice." Its care coaching screen detects early signs of cognitive decline mid-visit and surfaces a structured alert with actionable recommendations. These are fit signals, trust signals, change signals — exactly what agencies track through phone calls and coordinator intuition and nowhere else. The gap: Sensi requires hardware in the home, client consent to ambient audio, and works only post-placement at enterprise scale. But it's the first tool that treats what happens between caregiver and client as operational data worth capturing, not just a relationship too soft to measure.

Competitor insight: The competitive analysis rates end-of-care as the lowest-density moment in the entire agency lifecycle — almost no standalone tools, a checkbox in the ERP, no dedicated market. Sensi's Solo Care Dashboard is the closest attempt: it monitors seniors without a paid caregiver and surfaces real-time readiness tags — Ready for Blended Care, Check In Required, Steady — so coordinators can identify when someone is approaching a transition before a crisis forces it. It's the first tool treating end of care as a signal rather than a record. The gap: it requires Sensi hardware already in the home and only works within the Sensi ecosystem. For most agencies, end of care still means the relationship stops at the door and the family navigates the next transition alone.

Some ways AI tools could help wtih this. https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3ca731bc964_0_1148#slide=id.g3ca731bc964_0_1148

Riley answers every inbound call 24/7 and routes urgent issues by looking up patient info in the EMR. Casey Coordinator handles call-outs with 5-minute average resolution via SMS and voice — no app download required from caregivers. The current problem is caregivers calling clients directly to cancel because it's the path of least resistance — the agency is hard to reach after hours, the coordinator's personal number is what they have, and the client's number is easier. Riley eliminates that excuse entirely. There's always someone to call at the agency. The caregiver calls Riley, Riley handles the call-out, Casey finds coverage, the EMR updates, and the client gets notified through the agency — not through a direct caregiver-to-client call that the agency never sees.

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3cdaa87a7a6_0_76#slide=id.g3cdaa87a7a6_0_76

ElliQ points toward a different model. The family app sends a notification feed directly to the family's phone: Gabbie took her Vitamin D, Gabbie rejected the Blood Pressure medication, Gabbie didn't respond to the colonoscopy prep reminder. The family doesn't have to go looking — the information comes to them, in plain language, in the channel they already use. Family can also interact with the senior directly by sending messages to the device.

Competitor insight: WellSky's Family Room has Calendar, Invoices, Medications, To Do, Care Logs, and a People tab — five navigation categories, multiple permission levels, a post field, an Events section. It is a portal in the full sense of the word. In this research, 3 of 22 agencies saw any real engagement from family portals. The design asks families who are already anxious and already overwhelmed to log in, orient themselves, navigate to the right section, and look for what changed. The burden is on them.

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3cc0d0ff19c_0_15#slide=id.g3cc0d0ff19c_0_15

Competitor insight: WellSky's Care Log shows every task from a completed shift timestamped identically at 08:42 PM — assist with meal, dressing, toileting, transfers, bathing, brushing hair, brushing teeth, changing linens, cleaning the bathroom — all in a single batch, all marked Complete. The coordinator sees a green status. The billing system sees clean hours. What neither sees is whether any of it happened, or whether the caregiver toggled through the list at clock-out to get the app off her phone. The care plan was written at assessment. The care log was completed at shift end. Nothing in between — no notes, no flags, no signal about how the visit went — exists unless the caregiver proactively wrote it. The plan doesn't update. The relationship doesn't accumulate.

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3cc0d0ff19c_0_103#slide=id.g3cc0d0ff19c_0_103

Competitor Insight: WellSky Mobile app for caregivers shows a sterile overview of what the client needs, but little nuance on who the client IS. or how they got to this point/ what the familiy dynamics are.

They are also required to do an enormous amount of tracking in-app and provide reasons for why a task was not completed, which removes agency, degrades trust, and perpetuates a transactional relationship between client and caregiver as well as agency and caregiver.

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3cc0d0ff19c_0_37#slide=id.g3cc0d0ff19c_0_37

Screenshot: p.31 — AxisCare Care Notes

Competitor insight: AxisCare's Notes tab is designed to be the "institutional memory" for a client. On the left, a Permanent Priority Notes field holds free-text behavioral context — dementia, fall risk, eating difficulties. Below it, timestamped Client Notes accumulate from multiple staff members. On the right, a call log and tagged note archive. There is no intake brief, no structured summary from the referral source, no field that asks "what did the family tell us when they first called?" When an APFM referral arrives, neither AxisCare nor WellSky has a designated place for the family's story. The coordinator types what they remember into an unguided free-text field — or doesn't. It's not a training failure. The tool was never designed to receive or preserve referral-level narrative.

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3ccfe8791cf_0_38#slide=id.g3ccfe8791cf_0_38

Most care plans also don't retain the richness of the assessment- care plan templates used by wellsky and axis care, even if the NOTES are really good, end up being extremely limited to a list of tasks that a caregiver has to take

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3cc0d0ff19c_0_46#slide=id.g3cc0d0ff19c_0_46

WellSky Deep Dive: Care Log

Some tools are getting better: Screenshot: p.21 — WellSky SkySense AI WellSky's SkySense Scribe records the clinician's voice during a visit and auto-populates EHR fields in real time — saving 15–20 minutes on documentation that typically takes an hour.

The gap it doesn't close: SkySense captures what the clinician says during the assessment visit. It has no connection to what the family told APFM before the agency was ever involved. The upstream intake context still has nowhere to go. it also still compresses information into an AI template for care plan that probably doesnt include the nuance of the client or their needs.

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g395c49e4b00_0_71#slide=id.g395c49e4b00_0_71

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3cc0d0ff19c_0_15#slide=id.g3cc0d0ff19c_0_15

WellSky's Family Room has Calendar, Invoices, Medications, To Do, Care Logs, and People tabs — five navigation categories, multiple permission levels, a "What's on your mind?" post field, an Events section. It is a portal in the full sense of the word. Agencies report almost no one uses it. The design asks families who are already anxious and already overwhelmed to log in, orient themselves, navigate to the right section, and then look for what changed. The burden is on them.

ElliQ points toward a different model — the family app sends a notification feed directly to the family's phone: Gabbie took her Vitamin D, Gabbie rejected the Blood Pressure medication, Gabbie didn't respond to the colonoscopy prep reminder. The family doesn't have to go looking. The information comes to them, in plain language, in the channel they already use. The gap ElliQ hasn't closed is that it requires hardware in the home and still doesn't connect to the agency. But the interaction model is right: visibility that comes to you, not a portal you have to visit.

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3cc0d0ff19c_0_15#slide=id.g3cc0d0ff19c_0_15

Some tools are starting to close this gap. Sensi.AI's Care Coaching screen shows what a living care plan could look like — passive audio mid-visit detects that Henry has a potential medication risk and surfaces a structured alert to the coordinator with three specific actionable recommendations auto-generated: same-time daily dosing, a medication organizer, family call reminders. The care plan isn't a static document written once at assessment — the visit itself is generating signals that update what coordinators know and what should happen next. The gap it hasn't closed: it still requires hardware in the client's home, ongoing consent, and enterprise adoption. And it works post-placement, not at the moment the plan is being written. But it's the first tool that treats care planning as something that should evolve from what actually happens in the room.

https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3cdaa87a7a6_0_14#slide=id.g3cdaa87a7a6_0_14

Competitor insight: Some tools are starting to close this gap. CareSwitch's Looper uses voice dictation directly in the mobile app — a coordinator can talk through a client's needs during the visit, and Looper structures that raw audio into a drafted assessment in real time. It also offers AI-guided templates that prompt for compliance-required fields without forcing the coordinator off the conversation, and can auto-generate a care plan from the captured notes before they leave the house. For coordinators who still prefer to handwrite in the room, Looper can import those notes afterward and surface the most important clinical details. This is meaningfully different from the AxisCare approach — instead of asking the coordinator to choose between presence and documentation, it lets the voice carry both. The gap it hasn't closed yet is the same one paper hasn't closed: structured clinical capture is still not the same as preserving who the client is. But it's the first category of tool that treats the assessment as a conversation first and a form second.

Screenshot: p.24 — WellSky CareFinder

WellSky's CareFinder filters by skills, certifications, availability, and client attributes like pets and live-in. Its own slide documents how matching actually happens alongside the tool: the owner pre-matches mentally, owner and scheduler discuss soft fit, CareFinder filters constraints, the scheduler picks from memory — not the list. The tool is step three of a five-step process that begins and ends in someone's head.

Slide 24: https://docs.google.com/presentation/d/1pzOaYWtZE3qjPCy55tZlw00QbZsn_5pgWTMoqm56H3I/edit?slide=id.g3cc0d0ff19c_0_7#slide=id.g3cc0d0ff19c_0_7 WellSky's CareFinder filters by skills, certifications, availability, and client attributes like pets and live-in, not soft matching on personality or availability preferences. How it works Coordinator enters required hours and dates→ CareFinder returns caregivers filtered by skills, certifications, availability, and client-specific attributes (pets, live-in, car)

What It Misses Personality · communication style · emotional needs Physical strength fit ("Betty's too slight") Rapport history · age compatibility Whether a caregiver will stay when needed

add "our recommendation"