Promptic
Promptic is an AI optimization platform for GenAI applications. It helps teams benchmark models, tune prompts and agents, optimize extraction and tool use, and ship configurations that deliver the best quality, cost, and latency on their own data.
At a Glance
- Product teams shipping customer-facing AI features
- Engineering teams optimizing GenAI quality, reliability, latency, and cost
- Data and AI teams comparing prompts, models, evaluators, and agent designs
- Founders and operators moving GenAI workflows from prototype to production
- +1 more
AI Tools by Promptic
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Promptic
LLM Observability and Optimization Platform
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Latest News
Promptic Is Open to Everyone
Promptic launched on Product Hunt as an optimization platform for GenAI applications for quality and cost.
Tracing, Python SDK, and richer prompts release added OpenTelemetry tracing, Python SDK/CLI, train/test splits, multi-variable prompts, chat-message prompts, and configurable structured-output evaluation.
statworx announced a pre-seed investment in Promptic, founded by Daniel Schroter Thüm and Dominik Bura.
Products & Services
SaaS platform for benchmarking models and optimizing prompts, agents, extraction workflows, and MCP/tool selection against customer data and KPIs.
Automatically finds better prompts using customer examples, evaluators, and business metrics, with quality, cost, and latency comparisons.
Evaluates complete agents and compares outputs, artifacts, trajectories, and agent architectures on representative datasets.
Discovers tools from MCP servers and improves how reliably models select and use tools.
Market Position
Promptic positions itself as an optimization layer for the full GenAI stack rather than only a prompt editor or observability dashboard. It differentiates through a single evaluation loop that uses customer data and production traces to compare models, prompts, agents, extraction workflows, and tools on quality, cost, and latency. Adjacent competitors include prompt-management and evaluation platforms such as LangSmith, Braintrust, Humanloop, W&B Weave, and Arize Phoenix, while Promptic emphasizes automated optimization and shipping the best-value configuration.
Leadership
Founders
Daniel Schroter Thüm
Senior AI/ML Engineer and subject-matter expert for Agentic AI at statworx; his public profile also identifies him as co-founder of promptic.eu. He studied at the Technical University of Munich.
Dominik Bura
Co-founder of Promptic and managing director. Public announcements describe him and Daniel Schroter Thüm as having started their journey in statworx's AI Development team.
Executive Team
Daniel Schroter Thüm
Managing Director and Co-Founder
Senior AI/ML Engineer and Agentic AI specialist at statworx; co-author of Promptic's automated prompt-optimization material.
Dominik Bura
Managing Director and Co-Founder
Co-founder of Promptic; previously part of statworx's AI Development team according to the investment announcement.
Founding Story
Promptic was created to address the gap between GenAI prototypes and production systems: teams need evidence-based ways to decide which prompts, models, agent architectures, extraction workflows, and tool strategies perform best. Its founders describe the product as an optimization loop built around real examples, evaluations, production traces, and business metrics rather than manual prompt edits or intuition.
Business Model
Revenue Model
Subscription SaaS plans priced by organization/team access, AI Applications, Promptic Credits, retention, and governance; optional managed-model usage is billed separately, while customers can also bring their own model keys.
Pricing Tiers
1 user, 1 AI Application, 200K Promptic Credits per month, 14-day retention, and bring-your-own model keys.
Unlimited users, 1 AI Application included, 1M Promptic Credits/month, 30-day retention, BYOK or optional managed model usage, prompt optimization, evaluations, tracing, and API/SDK access.
Unlimited users, 5 AI Applications included, 5M Promptic Credits/month, 90-day retention, advanced optimization, trace evaluations, tracing, CI/CD gates, RBAC, and priority support.
Custom applications and committed credits, custom retention, SSO/SAML, SCIM, advanced RBAC, audit logs, SLA, dedicated support, and Private Cloud/BYOC options.
Target Markets
- Product teams shipping customer-facing AI features
- Engineering teams optimizing GenAI quality, reliability, latency, and cost
- Data and AI teams comparing prompts, models, evaluators, and agent designs
- Founders and operators moving GenAI workflows from prototype to production
- Enterprise organizations requiring governance, security, private cloud, or BYOC deployment
- Customer support and intent classification
- Sales assistants
- Content generation
- HR recruitment
- Legal review
- Information extraction and structured-output workflows