Off-script queries crashed Scout V1. One frontier model with access to 40M companies and firm context later, sessions run 10x longer.
A startup intelligence platform serving venture capital firms and private market investors, with a proprietary database of 40 million companies, 200 million people, and 230,000 investors.
Scout V1 could translate natural language into precise database filter configurations, but the architecture was rigid: any intent outside predefined...
“Before, we spent a lot of time building rigid structures, writing evals, and tediously iterating on every node. With this version, we said: let's use the best and smartest models, give it access to thoughtful tools that interface with our data, and see how Deep Agents does. And immediately we saw incredible improvements.”
AI startup discovery engine for venture capital and sales teams.
Framework and developer platform for building LLM-powered applications.
Harmonic's Startup research is part of this use case:
Related implementations across industries and use cases
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Dense API docs bottlenecked non-technical users. Now, Claude builds fully configured voice agents from simple plain-text requests.
One AE held the team's institutional knowledge—90% of his day in Slack. A digital double in his voice freed him to sell.
Analysts spent days building reports from slow, siloed tools. Now, they ask a question and an AI agent instantly generates an accurate chart.
A solo HR leader spent 45 minutes manually compiling multi-currency reports. Now, simple AI prompts extract the exact live data needed.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
Off-script queries crashed Scout V1. One frontier model with access to 40M companies and firm context later, sessions run 10x longer.
A startup intelligence platform serving venture capital firms and private market investors, with a proprietary database of 40 million companies, 200 million people, and 230,000 investors.
Scout V1 could translate natural language into precise database filter configurations, but the architecture was rigid: any intent outside predefined...
“Before, we spent a lot of time building rigid structures, writing evals, and tediously iterating on every node. With this version, we said: let's use the best and smartest models, give it access to thoughtful tools that interface with our data, and see how Deep Agents does. And immediately we saw incredible improvements.”
AI startup discovery engine for venture capital and sales teams.
Framework and developer platform for building LLM-powered applications.
Harmonic's Startup research is part of this use case:
Related implementations across industries and use cases
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Dense API docs bottlenecked non-technical users. Now, Claude builds fully configured voice agents from simple plain-text requests.
One AE held the team's institutional knowledge—90% of his day in Slack. A digital double in his voice freed him to sell.
Analysts spent days building reports from slow, siloed tools. Now, they ask a question and an AI agent instantly generates an accurate chart.
A solo HR leader spent 45 minutes manually compiling multi-currency reports. Now, simple AI prompts extract the exact live data needed.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.