Automate on events
React to webhooks and polling triggers the moment something happens.
- Predict
- Chain of Thought
- ReAct Agent
Integration
With DSPy in Aptlystar, you can:
DSPy is a framework for programming—rather than prompting—language models.
How teams use DSPy
Integrate with your DSPy programs over HTTP for LLM-powered predictions. Supports Predict, Chain of Thought, and ReAct agents. DSPy is the framework for programming—not prompting—language models.
What can you do with the DSPy integration? DSPy is a framework for programming—rather than prompting—language models. DSPy enables you to build interpretable and modular LLM-powered agents using Python functions, structured modules, and declarative signatures, making it easy to compose, debug, and reliably deploy language model applications. With DSPy in Aptlystar, you can: AptlyStar exposes 3 operations so teams can automate end-to-end processes without maintaining brittle scripts.
Compose DSPy with the rest of your stack using visual workflows and agents.
React to webhooks and polling triggers the moment something happens.
Insert, upsert, and patch objects so workflows stay synchronized automatically.
Archive, delete, merge, and reconcile records with guardrails and approvals.
Trigger downstream actions, alerts, and hand-offs when something changes.
Aggregate metrics, export datasets, and feed BI or agent summaries.
React to webhooks and polling triggers the moment something happens.
Ship AI workflows that read, decide, and act on DSPy — with guardrails and human approvals where you need them.
Build a workflow that reads raw records from a table, runs a DSPy predict program on your self-hosted server to extract structured fields from each, and writes the typed results back to the table.
Explore templatesCreate a workflow that runs a DSPy program against a labeled evals table, computes accuracy, F1, and per-class breakdowns, and writes the metrics to a reporting table for tracking over iterations.
Explore templatesCreate a scheduled workflow that runs two DSPy program endpoints against the same eval set nightly, scores each on accuracy, and writes the head-to-head comparison and recommended winner to a table.
Explore templatesBuild a workflow that periodically replays sample production traces through a DSPy program, captures divergences, and writes regression analysis to a tracking file.
Explore templatesCreate a workflow that runs a DSPy program over an eval set, logs each prediction as a LangSmith trace for evaluation, captures the quality delta against the previous run, and writes the comparison to engineering Slack.
Explore templatesCreate a workflow that takes a research question, uses DSPy chain-of-thought to break it into sub-questions, runs DSPy ReAct with web search to gather evidence, and writes a structured, cited answer to a file.
Explore templatesConnect DSPy once, then reuse the same blocks across agents, workflows, and templates.
Teams lose hours copying data between DSPy and CRMs, inboxes, and spreadsheets. AptlyStar connects DSPy to 3+ operations so updates flow automatically.
Learn moreOne-off scripts break when APIs change. Use visual workflows, retries, and typed blocks so DSPy automations stay maintainable as you grow.
Learn moreAgents need live DSPy context without over-permissioned keys. Connect credentials once, apply guardrails, and let agents act through audited workflow runs.
Learn moreReady-to-use workflow templates that include DSPy, just like in the app.
DSPy structured extraction
Build a workflow that reads raw records from a table, runs a DSPy predict program on your self-hosted server to extract structured fields from each, and writes the typed results ba...
DSPy evaluation harness
Create a workflow that runs a DSPy program against a labeled evals table, computes accuracy, F1, and per-class breakdowns, and writes the metrics to a reporting table for tracking ...
DSPy A/B program selector
Create a scheduled workflow that runs two DSPy program endpoints against the same eval set nightly, scores each on accuracy, and writes the head-to-head comparison and recommended ...
DSPy production traffic replay
Build a workflow that periodically replays sample production traces through a DSPy program, captures divergences, and writes regression analysis to a tracking file.
DSPy + LangSmith trace harness
Create a workflow that runs a DSPy program over an eval set, logs each prediction as a LangSmith trace for evaluation, captures the quality delta against the previous run, and writ...
DSPy ticket classifier
Build a workflow that runs new support tickets through a DSPy predict signature to classify category, urgency, and sentiment with structured outputs, then routes each ticket to the...
Design multi-step automations with blocks, branches, loops, and human-in-the-loop checkpoints — no boilerplate code.
Learn moreGive agents tools, memory, and guardrails so they can plan, call integrations, and finish tasks across your stack.
Learn moreGround agents in docs and tables, then trace every run with logs, evaluations, and deployment controls.
Learn moreA2A
Interact with external A2A-compatible agents
Browser Use
Run browser automation tasks
Stagehand
Web automation and data extraction
DeepSeek
Use DeepSeek models for chat and reasoning
Google Translate
Translate text using Google Cloud Translation
LangSmith
Forward workflow runs to LangSmith for observability
Anthropic Claude
Use Claude models for chat and reasoning
Azure OpenAI
Use Azure OpenAI deployments for chat and reasoning
Connect DSPy to agents and workflows in minutes — no credit card required.