Althio, INC.  ·  Pre-seed  ·  August 2026

Context engineering for
continuous care.

ConsultOS, the operating system for behavioral-health clinics. The context of care lives between sessions. Althio builds it.

Mariyam Vidhu Vijayan  ·  Rustum Usman

Origin

A clinic owner saw where care actually breaks.

Mariyam spent five years building and running an online therapy practice serving 20,000+ working professionals. The pattern she could not ignore: clients did their best work inside the session, then went quiet for a week. The therapy was sound. The space between sessions was empty.

That gap, not the quality of clinicians, is where outcomes are lost.

20,000+
professionals served across five years of clinical operations
1st
customer is our own clinic, Crink Pvt Ltd, operating the product today
The problem

A patient's life has three layers.
The session sees a fraction of the third.

Experienced
The whole of life
Everything the client actually lives through between sessions: sleep, conflict, work pressure, habits, the 2 a.m. spiral. Almost none of it is visible to the clinician.
Perceived
What they notice
The portion the client registers as meaningful: moods they can name, patterns they half-recognize, concerns they intend to raise but forget by Thursday.
Shared
50 minutes a week
What finally reaches the therapist: a compressed, recollection-filtered account delivered in a 50-minute window. The entire clinical record is built on this fraction.
Why now

Demand is enormous. Access is contracting.

29.5M
US adults with mental illness received no treatment in 2024
137M
Americans live in designated mental-health shortage areas
−10M
behavioral telehealth visits, 2023 → 2024, even as need rises

Medicaid contraction

Coverage retrenchment pushes behavioral health out of reimbursed channels.

Workforce growth, misallocated

Clinician headcount grows while utilization per clinician falls.

Platform capture

Large platforms absorb supply without fixing continuity of care.

AI absorbs first contact

Patients increasingly open up to AI before they ever reach a clinician.

The economic engine
$300K

lost every year to no-shows by a typical 10-clinician practice. A cash problem a clinic can identify in its own numbers within a week, not a quarter.

Outpatient therapy no-show rates run 18–30%. Every empty hour is clinician capacity already paid for and never recovered.

+22%
practice profit from attendance recovery alone
+20%
revenue from improved retention and freed clinician capacity
0
reimbursement codes required, sold on direct provider payment, not claims
2,530 hrs
empty slots a year to recover from no-shows and reallocate to the waitlist
The product

One system, two experiences.

The therapist

Freed from clerical work

  • Arrives already prepared, briefed by the AI on everything that happened since the last session
  • No session notes: AI transcribes and renders SOAP, DAP, BIRP, or custom templates
  • The whole picture mapped: problems, patterns, solutions, relationships, treatment methodology, action steps
  • A clinician copilot between sessions: assessment recommendations, treatment plans, any client detail on demand
  • Five-minute wrap: notes finalized and shared, claim filed, the therapist gets feedback on their own practice, thus ensuring consistent quality across all therapists in the clinic
The client

Care becomes continuous

  • AI follows up after every session, supporting action steps and activities
  • Relapse risk identified proactively; the next session is nudged before the client disengages
  • The week between sessions becomes part of the treatment, not a gap in it
  • Patterns from chat and wearable data surfaced to the therapist before the next session
  • Safety monitoring runs underneath everything, always human-anchored
The moat

Context,
engineered.

Work stress Sleep Manager conflict Marriage strain Morning walk Father's illness

One client, month 4. Node size is current weight. Thin dashed links are context that has not been reinforced.

Every client is a weighted context graph, not a case file. Client context carries weight as per current relevance. The AI does not summarize. It connects.

Two conversational streams

Client ↔ therapist sessions, transcribed. Client ↔ AI conversation, continuous. Both feed the same graph.

Multimodal signals

Watch data, phone usage, and other passive signals add a third stream no session transcript can capture.

Compounding, not portable

Every conversation makes the next one better. The graph is the asset, and it cannot be replicated by an episodic competitor.

This is what recovers the $300K. The same context that compounds into a moat is what keeps a client engaged through the week — and showing up on Thursday.

Clinically anchored

The hybrid human-therapy + AI-support model is corroborated by published clinical literature (Noto et al., Journal of Technology in Behavioral Science, 2026).

Which market, how money flows

A barbell market, entered on cash.

The market
TAM  ·  2026
$8–11B
TAM  ·  early 2030s
$16–20B
SAM  ·  per year
$1.5–3B

22–32K sellable organizations

Independent and group behavioral practices: big enough to feel the no-show loss, small enough to adopt without a hospital procurement cycle.

Direct provider payment, not reimbursement

We do not enter through CoCM (a primary-care instrument) or DMHT codes (~$20 per 20 minutes, gated behind FDA device clearance). Clinics pay directly for recovered attendance and capacity, the same cash motion that works internationally.

Why $100M is a density problem
01
$1.5–3B SAM ÷ 22–32K clinics
$47–136K per clinic, per year

Midpoint annual contract value about $92K.

02
$100M ÷ $92K
≈1,100 clinics = 3–5% of the country

A low single-digit share of the national sellable count. Market size is not the binding constraint.

Spread nationally
<3

clinics per metro across 387 US metros. No payer in any single market has to notice us.

20–30% of one metro
240

clinics in a large metro, so $100M arrives from four or five of them, as a network a payer cannot route its members around.

Same revenue, a different company. Density is what stage 1 trades for stage 2: clinic cash buys concentration, and concentration buys payer distribution.

Traction & funding climate

Early pull, in the strongest-funded category in digital health.

5–10

US psychologists in active discovery, pre-launch

2

chain opportunities in pipeline: a large Middle East hospital group and a 17-location clinic chain

1st

customer live: our own clinic operates the product daily, the proof and the reference

7 yrs

mental health has been the top-funded digital-health indication, seven years running

Talkiatry$210M Series D, Feb 2026
Grow Therapy$150M at $3B valuation, Mar 2026
Salma Health$80M Series A, Feb 2026
Jimini Health$17M seed, Mar 2026, the direct pricing comparable for this raise
Team

Operators who have run the clinic, built the product, and sold the motion.

CEO & Co-founder
Mariyam Vidhu Vijayan
Psychologist-operator. Built and ran an online therapy practice over five years serving 20,000+ professionals; the origin of the continuity thesis.
CPO & Co-founder
Rustum Usman
Product and go-to-market. MBA, IIM Kozhikode. Ex-consultant, ex-startup. Runs enterprise sales solo; architect of the context engineering model behind ConsultOS.
CGO
Krystal Williams
Growth. Ex-BCG, Cornell. Deep US healthcare and behavioral-health network; founding team member.
Software Architect
Eisa Usman
Architecture of the context engine and the AI copilot systems behind the therapist and client experiences.
Engineering Manager
Aqueel Ahmed
IIT. Leads product engineering across the ConsultOS platform and ML systems.
Product Engineer
Ajmal Roshan
Backend engineering on the ConsultOS platform; core contributor to the clinical data and integration systems.
Advisors
Smrithi Ravichandran
Investment Professional, Multiples Alternate Asset Management; former Flipkart VP. Growth strategy and investor networks.
Dr Sherbaz Bichu
CEO, Aster Hospitals & Clinics. Healthcare operations at scale; early investor and connector.
Dr Waheeda Khan
Professor Emeritus & Advisor, Clinical Psychology, SGT University; former Head of Psychology, Jamia Millia Islamia. Four decades of clinical academia.
Shahidh
Hasura & PromptQL. AI product and infrastructure.