LangChain

Observed profile

Agent-engineering platform for building, deploying, and operating LLM-powered applications.

As of , AIIStack tracks LangChain's Innovation score at 89.29/100, down 5.71 points.

Headquarters
Not disclosed
Founded
Founded year not disclosed
Official website
langchain.com
Compare Claim or correct
Agent frameworks

Cohort-normalized indicators

Company scorecard

Innovation score
89.29/100
Change
5.71 pts
Interpretation
Current cohort score
Popularity score
89.29/100
Change
0 pts
Interpretation
Current cohort score
Momentum score
89.29/100
Change
5.71 pts
Interpretation
Current cohort score

Activity timeline

Material changes

Updated
GitHub release
Notable

langchain-ai/langchain released langchain-core==1.7.0

Source: Source evidence98% confidence
GitHub release
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langchain-ai/langchain released langchain==1.4.7

Source: Source evidence98% confidence
GitHub release
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langchain-ai/langchain released langchain-core==1.6.13

Source: Source evidence98% confidence
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langchain-ai/langchain released langchain-perplexity==1.4.2

Source: Source evidence98% confidence
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langchain-ai/langchain released langchain-core==1.6.12

Source: Source evidence98% confidence
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langchain-ai/langchain released langchain-core==1.6.11

Source: Source evidence98% confidence
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Notable

langchain-ai/langchain released langchain-openai==1.7.2

Source: Source evidence98% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-anthropic==1.7.6

Source: Source evidence98% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-openai==1.7.1

Source: Source evidence98% confidence
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Notable

langchain-ai/langchain released langchain-core==1.6.10

Source: Source evidence98% confidence
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langchain-ai/langchain released langchain-fireworks==1.7.1

Source: Source evidence98% confidence
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Notable

langchain-ai/langchain released langchain-huggingface==1.2.3

Source: Source evidence98% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-core==1.6.7

Source: Source evidence98% confidence
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langchain-ai/langchain released langchain-text-splitters==1.1.3

Source: Source evidence98% confidence
GitHub release
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langchain-ai/langchain released langchain-openai==1.6.7

Source: Source evidence98% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-anthropic==1.7.5

Source: Source evidence98% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-core==1.6.6

Source: Source evidence98% confidence
Mention spike
Notable

18 new attributable Hacker News discussions were observed in the last seven days.

Source: Source evidence78% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-fireworks==1.7.0

Source: Source evidence98% confidence
Source update
Monitor

LangSmith Cloud changelog - Docs by LangChain changed

Source: Source evidence70% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-fireworks==1.6.3

Source: Source evidence98% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-core==1.6.5

Source: Source evidence98% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-openai==1.6.6

Source: Source evidence98% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-anthropic==1.7.4

Source: Source evidence98% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-openai==1.6.5

Source: Source evidence98% confidence
Mention spike
Notable

8 new attributable Hacker News discussions were observed in the last seven days.

Source: Source evidence78% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-typesafe==0.0.1a3

Source: Source evidence98% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-typesafe==0.0.1a2

Source: Source evidence98% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-typesafe==0.0.1a1

Source: Source evidence98% confidence
Mention spike
Notable

16 new attributable Hacker News discussions were observed in the last seven days.

Source: Source evidence78% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-core==1.6.3

Source: Source evidence98% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-anthropic==1.7.2

Source: Source evidence98% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-openai==1.6.2

Source: Source evidence98% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-openai==1.6.1

Source: Source evidence98% confidence
Mention spike
Notable

25 new attributable Hacker News discussions were observed in the last seven days.

Source: Source evidence78% confidence
GitHub release
Notable

langchain-ai/langchain released langchain-core==1.6.2

Source: Source evidence98% confidence

Discussion intelligence

Recent Hacker News mentions

All market discussions
story
3 points

Show HN

This is origintracer a low level observability tool of the modern web stack. It observes nginx, Gunicorn, asynchronous Python, Uvicorn and Django and Langchain. Studies their codebases into great depth and write probes and rules libraries in Python to be used with the open source software: its link GitHub: https://github.com/Humbulani1234/origintracer

Inspect discussion
comment

DSPy – Program, don't prompt, your LLMs

is this pretty close to langchain / ADK? this looks to generate prompts with words/instructions not provided by the user, not keen on that concept

Inspect discussion
comment

Stripe's Knowledge AI Platform

> This sounds more like a criticism of older versions of LangChain than its current APIs Oh no worries, I'm always happy when library / sdk makers are constantly changing their APIs in-between versions. Why would I not want to spend time updating my code to return to baseline functionality when I could have just built something using the 4-year stable underlying chat completions API instead...?

Inspect discussion
comment

For Computer Use, the harness matters as much as the model

Hi HN, Over the last 2 years, we observed computer use models improving at a rapid pace and saturating benchmarks. This new benchmark replaces Online-Mind2Web with our own Browserbase Benchmark v2 that better represents the complex tasks that browser agents face in the real world. It runs against 23 models (frontier and open-weight) and 9 harnesses (Claude Code to LangChain Deep Agents) on accuracy, speed, and cost. This new benchmark confirmed our belief that the choice of an harness is becoming as important as the choice of a model. For example: claude-opus-5 runs 74% at $1.50/task on LangChain deep agents but 71% at ~$10/task on fx. The eval harness is a CLI you can run yourself (pick harness + tools/mcps + model, pass high-level tasks, grades with LLM verifiers, has tri…

Inspect discussion
comment

Stripe's Knowledge AI Platform

Creating deep research multiagent systems without explicitly handing it a file system is a terrible idea. The only successful way we have found to reliably hand off context in multiagent systems is using a file system. Langchain even today doesnt make that default or even encourage it.

Inspect discussion

Public discussion records are evidence of conversation, not a sentiment or product-quality verdict.

Source-backed company graph

Documented relationships

These are directed, attributable graph assertions—not inferred similarity or paid placement.

alternative

LlamaIndex is documented as alternative to LangChain.

88%
alternative

LangChain is documented as alternative to LlamaIndex.

88%

Competitive context

LangChain alternatives and competitors to monitor

LlamaIndex

llamaindex.ai

Agentic document and data platform for knowledge-grounded AI applications.

Agent frameworks
Popularity score
83.57/100
Score change
0
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