Wearables flood you with raw biometric noise, leaving you to guess what to execute next. biosynth.app cuts through the telemetry noise to deliver an authoritative, verified morning training directive. Architected on the full Claude 5.5 Tri-Tier hierarchy (Claude Opus 5.5 for Tier 3 deep longitudinal mesocycle periodization and sustained biological judgment, Claude Sonnet 5.5 for multi-agent reasoning, synthesis, and 70.6% Terminal-Bench 4.0 tool execution, and Claude Haiku 5.5 for rapid telemetry triage, streaming conversational follow-up, and sub-second classification) aligned with the production roadmap for Claude Managed Agents alongside LangGraph multi-agent state machines, paired with an instant System 1 biomechanical engine, it translates heart rate variability, sleep stages, and tendon load into daily workout adaptations directly compatible with your Garmin ecosystem (Dual-Track: operational standalone .FIT generation today, official Garmin Health Developer API undergoing enterprise review) and precision nutrition targets.
Garmin Cloud Synced: 06:15 AM
"Full physiological readiness confirmed. Scheduled workout: 5 x 1000m Threshold Intervals (Zone 4 @ 3:45/km) synced directly to your Garmin watch. Recommended carbs: 60g/h, with elevated sodium intake adapted to forecasted 14°C ambient conditions."
Why Generic LLMs Fail at Human Physiology
Your watch records millions of heartbeat intervals. But standard conversational chatbots either hallucinate arithmetic calculations or emit dangerous, ungrounded medical claims.
Raw language models struggle with rolling biometric formulas and multi-week training load ratios. Translating calculations into executable code rather than predicting text tokens improves complex tabular health reasoning by up to 29.6% (EHRAgent, EMNLP 2024) — eliminating numerical hallucinations through BIOSYNTH's isolated deterministic math sandbox.
Downloaded PDF plans or static calendar entries do not care that you slept 3 hours or your HRV plunged 30% after an immune reaction. Pushing through leads directly to overtraining and injury.
Unconstrained bots claim to "diagnose illnesses" or prescribe clinical regimens. biosynth.app strictly enforces deterministic non-clinical boundaries informed by multi-agent safety research (CareGuardAI, CLEVER) — immediately intercepting diagnostic queries and focusing strictly on sports science coaching.
Thin API wrappers and simple prompt relays fail when confronted with noisy, multi-week physiological time-series. Biosynth establishes a resilient engineering moat through our 3-Tier DeepTech Architecture, decoupling raw token volume from deterministic health intelligence:
Zero-knowledge hardware cryptography and local-first SQLite biometric storage. Raw athlete telemetry never leaves user-controlled enclaves in the clear, ensuring full compliance with GDPR and medical data sovereignty.
All rolling ACWR calculations, sweat rate formulas, and glycogen expenditure modeling execute inside an isolated Pandas numerical sandbox. Zero arithmetic token hallucination with verifiable sub-15ms execution.
Orchestrated with ISO 14971-informed non-clinical safety guardrails. Aggressive Prompt Caching and cascaded triage shrink production token costs to a sustainable $3–$8 / month per athlete.
How Our Specialized AI Agents Collaborate
Instead of relying on a single generic AI trying to do everything at once, biosynth.app coordinates specialized digital experts across the complete Claude 5.5 Tri-Tier hierarchy: Claude Opus 5.5 (Tier 3 deep longitudinal mesocycle periodization and sustained biological judgment), Claude Sonnet 5.5 (multi-agent reasoning, synthesis, and 70.6% Terminal-Bench 4.0 tool execution), and Claude Haiku 5.5 (rapid telemetry triage, streaming conversational follow-up, and sub-second classification) aligned with the Claude Managed Agents and LangGraph production roadmap.
Listens to your goals, tracks off-training physical stress, and dispatches tasks to specialist agents.
When you talk to the coach or log a change in your plans, the Orchestrator analyzes your message. If you did manual labor in the afternoon or slept poorly, it flags this hidden fatigue so the Trainer agent knows to adjust interval targets.
Athletes don't read lengthy reports while tying their running shoes before a 6:00 AM workout. biosynth.app delivers a concise 45-second morning audio briefing directly through your headphones via ElevenLabs voice synthesis—giving you an instant, high-energy coaching directive instead of forcing you to decipher complex data screens.
ElevenLabs Voice AI • Kevin Voice Model
A single day's snapshot doesn't tell the full story. biosynth.app evaluates how weeks of training load, nocturnal heart rates, and daily stress accumulate over time, giving athletes and coaches clear visibility into true recovery curves.
Test the Autonomous Decision Simulator
See how our Autonomous Governor recalculates training intensity in real time. Choose a preset or adjust the physiological levers below to test how the system reacts.
"Full physiological readiness confirmed. Workout approved: 5 x 1000m Threshold Intervals @ 3:45 pace with Progressive Overload."
Target fluid intake: 500 ml/h with baseline 400mg sodium. Fueling: 60g carbs/h.
Watch our System 1 decisional engine parse natural-language athlete directives into Garmin FIT SDK structures with sub-15ms deterministic matching and automated joint/tendon offloading substitutions.
Language models excel at understanding nuanced athlete instructions, but must never guess biomechanical parameters. biosynth.app utilizes a rigorous two-step verification: Step A: Claude 5.5 parses your natural training intent into a structured Model Context Protocol (MCP) tool call. Step B: The deterministic System 1 engine resolves exact Garmin FIT step parameters and tendon protection rules in sub-15ms with 0 tokens and zero hallucinations.
Zero musculoskeletal risk flags identified in prompt. Automated training parameter check complete — not a clinical or medical clearance.
{
"workout_name": "Threshold_5x1000m",
"sport": "running",
"sub_sport": "generic",
"steps": [
{
"step_type": "warmup",
"intensity": "active",
"duration_type": "distance",
"duration_val_meters": 1500,
"target_type": "heart_rate_zone",
"target_zone": 2
},
{
"step_type": "repeat",
"repeat_count": 5,
"work": {
"duration_val_meters": 1000,
"target_type": "pace",
"target_pace_str": "3:45/km"
},
"recovery": {
"duration_val_meters": 200,
"intensity": "recovery"
}
},
{
"step_type": "cooldown",
"duration_val_meters": 1000,
"target_zone": 1
}
]
}
Direct binary compilation via standalone FIT generator engine.
Watch how an unstructured athlete check-in is received by the Orchestrator (Claude Sonnet 5.5), decomposed via Model Context Protocol (MCP) into three specialized sub-tasks across deterministic tools and sandboxes, and synthesized into an injury-safe Garmin training directive.
Real-world endurance coaching requires multi-domain reasoning: autonomic sleep recovery, tendon kinematics, and glycogen thermodynamics. Rather than relying on a monolithic prompt, Biosynth executes a typed state graph (LangGraph) where Claude Sonnet 5.5 acts as the central conductor, spinning up focused worker sub-tasks with isolated tool privileges and recombining their conclusions into a deterministic output.
Claude Sonnet 5.5 • Telemetry Synthesis
System 1 Matcher • Sub-15ms (0 Tokens)
Deterministic Pandas • Zero Hallucination
Multi-Modal Sync: Text Directive + Voice AI + Garmin .FIT Binary
Frontier Partner Stack & Architectural Ecosystem
Architected from the ground up for frontier AI reasoning and scalable endurance analytics. Here is how our multi-agent pipeline maps across partner technologies:
Claude Opus 5.5 (Tier 3 mesocycle periodization & biological judgment), Claude Sonnet 5.5 (multi-agent synthesis, 70.6% Terminal-Bench 4.0), and Claude Haiku 5.5 (rapid triage, sub-second classification).
Hands-free 45-second pre-run audio briefings and real-time audio debriefings for runners and cyclists.
Petabyte-scale telemetry time-series repository for high-density biometric streams and cadence metrics.
Physiological data science and interactive analytical notebooks modeling longitudinal recovery curves.
Automated PubMed EBM literature ingestion to continuously refresh sports science and exercise models.
Operational standalone .FIT generation today; official Garmin Health Developer API (Developer API Track) undergoing enterprise review.
Built by Athletes & Systems Engineers
We don't build abstract AI demos. We build the daily physiological co-pilot we rely on before 6:00 AM track workouts, grounded in evidence-based exercise science and local-first data privacy.
Lead Systems Architect & Founder • Project Architect
Project architect leading autonomous multi-agent orchestration, LangGraph state machines, local-first cryptography, Model Context Protocol (MCP), and isolated numerical execution. Sub-3 marathoner and endurance cyclist.
Applied Exercise Physiology & Safety Lead
Biomedical and physiological specialist guiding physiological telemetry interpretation, acute-to-chronic workload (ACWR) safety margins, overnight HRV baseline normalization, and ACSM non-clinical compliance filters.
Referencing Anthropic's 'The Claude Code Guide For Startups'
Biosynth's entire agentic architecture, deterministic mathematical sandboxes, and automated suite of 920+ unit & integration tests (921 passing) are built, refactored, and verified with Claude Code CLI (referencing Anthropic's 'The Claude Code Guide For Startups'). By operating Claude Code directly in deterministic headless loops, our engineering pipeline enforces strict cyclomatic complexity bounds (CC ≤ 10 across decision modules), architectural boundaries, sub-15ms execution guarantees, and ISO 14971-informed non-clinical safety guardrails.
Tested daily by amateur sports hobbyists and semi-pro endurance competitors.
During a 6-week half-marathon mesocycle, shifting hard interval quality to days with positive HRV z-scores produced a 3.8% increase in threshold pace with zero overtraining interruptions (individual case observation, self-reported/consented, non-controlled).
For everyday hobbyists, delivers elite daily physiological load adaptations and autonomous recovery vetoes previously only accessible through dedicated 1-on-1 human coaching costing $250–$600/month.
Early exploratory prototyping reached ~$100/mo per active athlete on unoptimized frontier models. In production, cascading routing (routing up to 80% of telemetry triage and conversational follow-ups to Claude Haiku 5.5) combined with Dynamic Prompt Caching and deterministic System 1 offloading drives projected inference down to $3–$8 USD / month per user. This achieves a sustainable 30–80x cost advantage over traditional human coaches ($250–$600/mo), ensuring resilient enterprise-grade unit economics at scale.