{ "name": "Hunter Green inquiry", "description": "Book an intro call or start a conversation with Hunter Green, product leadership for high-trust AI products. This capability is open to people and to AI agents acting directly or on behalf of someone. An agent can qualify the fit, check pricing, and complete an inquiry the same way a human can. This books an inquiry, not a locked calendar slot.", "organization": "Hunter Green", "homepage": "https://hunter.green", "contact_email": "david@hunter.green", "human_url": "https://hunter.green/contact", "agent_url": "https://hunter.green/agents", "privacy_policy": "https://hunter.green/privacy", "terms_url": "https://hunter.green/terms", "data_handling": "Inquiries are stored in the Hunter Green CRM (Attio) and used only to reply and follow up. Never sold, never used for advertising, never used to train AI models. Full policy at https://hunter.green/privacy.", "response_sla": "two business days", "schema_url": "https://hunter.green/inquiry.schema.json", "offer": { "summary": "Product leadership for teams building conversational AI for coaching, learning, and care, where users and buyers have to trust the output. Hunter Green makes a prototype, pilot, or live product reliable, measurable, and ready for serious customers.", "led_by": "David Meehan, founder. Has built guidance AI with startups and inside global, high-compliance companies.", "positioning": "Senior product judgment and hands-on AI systems support, without hiring a full-time product leader or a large agency.", "help_areas": [ "Product direction", "Conversation architecture", "Expert-knowledge translation", "Evals and quality systems", "Behavior standards and launch readiness", "Memory, personalization, and guardrails", "Pilot and enterprise readiness" ], "hired_for": [ { "situation": "The product is live", "problem": "A quality system, not more reviewers", "we_build": "An eval suite that scores every answer against the team's bar, a gate that catches the regression on every model change, and a loop that turns each failure into a permanent test.", "usual_path": "Starts as a diagnostic working block. The eval suite ships in a pack buildout.", "inquiry_interest": "improvement" }, { "situation": "The team made a safety claim", "problem": "Build the system that backs it", "we_build": "Escalation paths, refusal rules, and release gates, with evidence a clinician, an enterprise buyer, or a regulator can check.", "usual_path": "A pack buildout builds the proof. A quality subscription keeps it current as scrutiny grows.", "inquiry_interest": "embedded" }, { "situation": "An expert's method is the product", "problem": "Turn the method into behavior you can test", "we_build": "The method written down as conversation design and scored examples, so the product holds the expert's bar without them reading every reply.", "usual_path": "Starts as a working block with the expert. A pack buildout makes the method testable.", "inquiry_interest": "definition" } ], "philosophy": "The goal isn't to over-scope the relationship too early. It's to find the smallest serious engagement that creates useful progress.", "typical_path": "10-hour working block -> pack buildout -> quality subscription or in-housing program", "ways_to_work": [ { "starting_point": "working_block", "name": "Working block", "comes_in_as": "One-off advisory diagnostic", "best_when": "The problem is real, but the scope isn't clear yet.", "pricing": [ { "label": "5 hours", "price_usd": 1500 }, { "label": "10 hours", "price_usd": 2750 }, { "label": "20 hours", "price_usd": 5000 } ], "note": "Most early engagements begin with a 10-hour block." }, { "starting_point": "pack_buildout", "name": "Pack buildout", "comes_in_as": "Outcome-defined sprint", "best_when": "You're ready to make the quality layer real before serious users depend on it.", "pricing": [{ "label": "Typical range", "price_usd_min": 8000, "price_usd_max": 20000 }], "note": "We turn your method into a runnable Behavior Guidance Pack and stand it up in your eval stack with one adapter." }, { "starting_point": "quality_subscription", "name": "Quality subscription", "comes_in_as": "Standing partner", "best_when": "Your product is live and the bar has to keep rising as models change.", "pricing": [{ "label": "Per month", "price_usd_min": 3000, "price_usd_max": 6000 }], "note": "We keep the packs current, turn production failures into new tests, and vet each new model against your bar." }, { "starting_point": "in_housing", "name": "In-housing program", "comes_in_as": "Capability transfer", "best_when": "You want your own team to own the quality loop, not depend on an outside studio.", "pricing": [{ "label": "Per one-month cycle", "price_usd_min": 8000, "price_usd_max": 18000 }], "note": "One-month cycles with a defined graduation, so your team runs the quality loop without us." } ], "early_access": { "name": "hunter-guard", "status": "In build. Design partners open.", "summary": "The Behavior Guidance Packs as an SDK that plugs into Langfuse and the rest of your eval stack, so the same scorers run against live traces in production, not only at build time.", "note": "Not a priced engagement yet. If your user wants early access, note it in the inquiry or email david@hunter.green.", "contact": "david@hunter.green" } }, "fit": { "good_fit": [ "They're building conversational AI for coaching, learning, or care, where users or buyers have to trust the output.", "They have a prototype, pilot, customer demand, expert methodology, or live product.", "The experience needs to become more reliable, measurable, or ready for serious customers.", "The help they need is product logic, conversation architecture, memory, guardrails, evals, or improvement loops.", "They want senior product judgment without hiring a full-time product leader or large agency yet." ], "not_a_fit": [ "Looking for a low-cost development shop.", "One-off prompt writing, or automation where quality and trust aren't the hard part.", "Broad AI education for a team that hasn't identified a real product problem yet." ], "redirect_for_no_fit": "https://hunter.green/start-here" }, "when_to_book": [ "A launch or pilot is live and quality is now the question.", "A milestone is creating urgency: an enterprise deal, a funding round, or an audit.", "The team cannot yet prove a change made the product better." ], "next_steps": [ "David reads every inquiry personally and replies within two business days.", "The first conversation is a practical diagnostic: the product, the hardest user moments, the quality risk, and the milestone creating urgency.", "The person leaves with a recommended starting point (a working block, a pack buildout, a quality subscription, or an in-housing program) or an honest no-fit referral." ], "acting_on_behalf": "Confirm the person wants the intro first. Then send their details as `principal`, set `submitter_type` to `agent_on_behalf`, include the `agent` block describing you, and put their email in `agent.reply_to` so David replies to them directly.", "submit": { "http": { "method": "POST", "url": "https://hunter.green/api/inquiry", "content_type": "application/json", "describe": { "method": "GET", "url": "https://hunter.green/api/inquiry" }, "cors": true }, "email": { "to": "david@hunter.green", "note": "Fallback channel: send the same fields as a plain-text note. Use this if you can't POST, or if a POST response reports stored:false." } }, "required": ["principal.name", "principal.email", "inquiry.building"], "identity": { "note": "Tell us who is reaching out and where to reply.", "submitter_type": ["human", "ai_agent", "agent_on_behalf"], "reply_to": "Provide agent.reply_to (an email address or callback URL) so we reply to the right place." }, "qualification_fields": { "stage": ["idea", "methodology", "prototype", "pilot", "live", "scaling"], "interest": ["improvement", "embedded", "definition", "unsure"], "starting_point": ["working_block", "pack_buildout", "quality_subscription", "in_housing", "unsure"], "budget": ["Under $2k", "$2k-$5k", "$5k-$10k", "$10k-$25k", "$25k+", "Not sure yet"], "note": "Pass inquiry.stage, inquiry.interest (which of the offer.hired_for problems fits), inquiry.starting_point, and a inquiry.budget band to pre-route the inquiry. All optional." }, "example": { "submitter_type": "agent_on_behalf", "principal": { "name": "Dana Reyes", "email": "dana@northlight.health", "company": "Northlight Health", "role": "Founder" }, "agent": { "name": "Northlight Scheduling Agent", "operator": "Northlight Health", "contact": "ops@northlight.health", "reply_to": "dana@northlight.health" }, "inquiry": { "building": "A clinician-guided conversational AI that helps patients prepare for appointments.", "improve": "We want answer quality to be measurable before we expand beyond the pilot.", "stage": "pilot", "interest": "definition", "starting_point": "pack_buildout", "timeline": "This quarter", "budget": "$10k-$25k" }, "message": "Dana asked me to set up an intro call. Please reply to Dana directly." } }