Artificial Cognition & HAI
Interfaces where AI + humans make better decisions.
Use this for
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You’re adding AI features to neuro/psych products and need inspectable behavior.
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Teams want explanations, uncertainty, and refusals users actually understand.
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You must design handoffs (to clinicians/support) and guardrails that work in reality.
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Leadership/regulators ask for traceable decisions and clear limits.
What you walk away with
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HAI architecture map — who/what decides, when; human-in-the-loop points; audit trail.
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Interaction patterns — explanation surfaces, uncertainty display, refusal & escalation flows.
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Guardrail policies — red-teaming cases, block/allow rules, crisis off-ramps, content boundaries.
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Evaluation harness — task success, hallucination/claim error, refusal appropriateness, satisfaction.
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Model behavior spec — prompts/tools, retrieval/verification steps, test suites & edge-case library.
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Docs you can ship — model card, HAI rationale, safety memo, monitoring dashboard definitions.
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Copy deck — bias-aware microcopy for consent, warnings, instructions, and empty/error states.
Patterns we reach for
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Retrieve → Verify → Decide (RVD): evidence first, then a claim; uncertainty triggers handoff.
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Progressive explanation: quick “why” with deeper drill-down; no cognitive overload.
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Uncertainty-forward UI: calibrated scores, don’t-know states, and safe defaults.
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Refusal as a feature: clear “no” with next-step options and escalation routes.
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Boundary patterns: redaction/proxy for PII, tool-use over hidden memory, change-control notes.
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Outcome-first prompts: few-shot anchors tied to decisions.
Quality gates
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Critical-task success: ≥ 90% (with mitigations documented for the rest).
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Hallucination/claim error budget: ≤ agreed threshold on offline + shadow data.
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Refusal behavior: ≥ 95% correct refusals on disallowed/risky asks; ≤ agreed false-refusal rate.
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Calibration: ECE/BSR within target; uncertainty surfaced in UI & logged.
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Latency budget: p95 within target for each task; fallbacks specified.
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Traceability: inputs, sources, outputs, and human touches answerable in minutes.
Rapid · 2–3 weeks
HAI framework & guardrails
- Risk & task map, RVD flow, refusal/escalation logic, explanation wireframes.
- Red-team set + first evaluation pass (hallucination, refusals, latency).
- Decision memo: ship, sandbox, or fix (and how).
Build · 6–8 weeks
Pilot HAI (integrated)
- Implement interaction patterns (web/mobile/desktop), retrieval/verification steps, monitors.
- Model card, safety memo, dashboard spec, and A/B-ready copy.
- Usability + behavior readout with targets hit (or gaps named and sized).
Oversight (Monthly)
Evidence-in-use
- Incidents/refusals review, drift & calibration checks, eval set refresh, change-control notes.
- UX and prompt/tool tweaks tied to metrics; “stop-ship” triggers maintained.
Example runs
Eligibility assistant: rules-grounded screening with citations, uncertainty gating, and handoff.
Clinician support: explanation surfaces + calibration for signal-derived flags (EEG/HRV/EDA).
Adverse-event triage helper: detects risk language, refuses diagnosis, escalates to safe channels.
Boundaries
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We won’t build unsupervised diagnosis
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No crisis lines; we design escalations—operations will need to stay with your clinical/safety team.
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Privacy wins: PII boundaries and data retention are part of the design.
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Turn clever models into careful products.
Turn ideas into results that travel.
Book a 15-minute consultation or ask for an HAI sample pack.
FAQ
Which models do you support?
Modern LLMs and classic ML stacks; retrieval-first designs; we use your infra or help you choose.
Do you fine-tune the model or just the UX?
Both where needed, but interaction & evaluation lead. Heavy modeling lives under AI, Modeling & Data Science.
How do you measure “hallucination”?
Task-specific claim checks (sources/ground truth), offline red-team sets, and shadow runs in production.
Multilingual ready?
Yes—copy variants, comprehension checks, and locale-specific refusal/explanation patterns.
Will this satisfy regulators?
We align to your claims and produce the traceability reviewers expect; formal submissions sit with Regulatory & Clinical Evidence.
Need Some Help?
Feel free to contact us for any inquiry or book a free consultation.
