Where ELI agents create value
Practical, bounded applications across research, knowledge work, and Human + Agent collaboration.
Research acceleration
Synthesize evidence and compress discovery cycles.
Business intelligence assistance
Turn dashboards and data into clear signal.
Digital knowledge work
Draft, analyze, and maintain knowledge at scale.
Human cognitive offload
Track context and anticipate useful next steps.
AI literacy & workforce readiness
Help Crews adopt agents responsibly.
Agent evaluation labs
Measure reliability, safety, and capability.
Multimodal analysis
Reason over text, images, screens, and video.
Browser & desktop automation support
Operate real software with bounded action.
Content intelligence
Extract structure and meaning from content.
Evidence-first answering systems
Answers backed by verifiable proof.
How ELI Labz validates outcomes for PTSD and Autism use cases
A reproducible template we fill out for every supportive-technology deployment. Human owners keep authority; the agent operates inside bounded, verifiable loops with an open trace.
Context & goal
What outcome are we trying to support, and for whom?
PTSD support example
Support grounding and continuity of care between clinician visits for adults with PTSD, without providing diagnosis or treatment.
Autism support example
Support routine, sensory pacing, and communication scaffolds for an Autistic adult and their chosen support network.
Participants & oversight
Who is in the loop, and who has final authority?
PTSD support example
Licensed clinician as primary owner, individual as consenting participant, ELI agent as assistant. Clinician approves every care-adjacent action.
Autism support example
Individual as primary owner of their own plan, chosen supporters as reviewers, ELI agent as assistant. Individual approves any shared summary.
Method (observe - reason - act - verify)
What exact loop does the agent run, with what bounds?
PTSD support example
Agent observes logged check-ins, reasons over patterns using an evidence-linked memory, suggests grounding routines from a clinician-approved library, and verifies each suggestion against consent and safety rules before showing it.
Autism support example
Agent observes routine and sensory logs, reasons over the individual's own stated preferences, suggests pacing and communication prompts from a self-curated library, and verifies against a do-not-suggest list before showing it.
Outcome measures
How do we know it worked - quantitatively and qualitatively?
PTSD support example
Adherence to agreed grounding routines, self-reported distress before/after check-ins, clinician review notes, and rate of appropriate escalations. Measures are chosen with the clinician, not by the agent.
Autism support example
Self-reported comfort with daily routine, count of successful communication scaffolds used, and reduction in unwanted sensory overloads. Measures are chosen by the individual.
Reproducibility
Can another lab or clinic rerun this and get comparable results?
PTSD support example
Published protocol, versioned prompt and policy files, seeded evaluation set, and an open changelog. Every agent action stores the model version, tool calls, and evidence used.
Autism support example
Published protocol, versioned prompt and policy files, and an open changelog. The individual can export their full agent trace at any time.
Safety & failure modes
What must the agent never do, and how do we catch it if it tries?
PTSD support example
Agent never diagnoses, never changes medication guidance, never initiates crisis contact autonomously. Crisis language routes to a human path; every refusal is logged and reviewed.
Autism support example
Agent never overrides stated preferences, never shares data outside the chosen support network, never labels behavior as disordered. Every refusal and override is logged.
Evidence & traceability
What proof do we keep that each outcome is real?
PTSD support example
Immutable event log, linked source snippets for every suggestion, and a signed weekly report the clinician can accept, amend, or reject.
Autism support example
Immutable event log the individual owns, linked source snippets for every suggestion, and a weekly self-review the individual accepts, amends, or discards.
Iteration & learning
How does the system improve without drifting from the original goal?
PTSD support example
Changes proposed via a review board that includes clinicians; agent updates ship behind a flag with an A/B evaluation against the seeded set before general use.
Autism support example
Changes proposed by the individual and their chosen reviewers; agent updates ship behind a flag with the individual's explicit opt-in.
Supportive technology only. ELI Labz systems are not medical devices and do not diagnose, treat, or replace licensed clinicians, therapists, or caregivers.