AI and automation
LangChain in SIDECUBE digital projects
LangChain helps to prototype and orchestrate AI flows with models, tools, documents and processing steps.
Match
When we use LangChain
The technology is chosen after we understand the objective, the rhythm of the team, the level of administration and how much the project needs to increase.
- AI assistantsWe define what questions can be asked, what sources they use, and when a person has to intervene.
- RAGWe link the assistant's responses to the selected documents, with defined sources and usage limits.
- Document automationWe connect receipt, data retrieval and document verification to the next work steps.
- Tooled flowsWe define which operations the assistant may request and which validations are required prior to their execution.
Uses
What can we build with LangChain
We only use technology where it helps the project to be faster, easier to manage or safer to expand.
Deliverables
What goes into implementation
Accurate delivery depends on the project, but we keep every documented, tested and prepared implementation for maintenance.
- AI Flow Architecture
- Template connection
- Rules and validations
- Logs
- Scenario testing
Connected services
LangChain usually appears in these projects
Choose the service that best describes your need, then determine if this technology is the right choice.
AI AutomationSee serviceCustom softwareSee service
AI Automation
AI agents, document processing and automation connected to real processes, with rules, logbooks and human verification.
Software solutions
Applications, dashboards and integrations that gather important processes into a more manageable system.
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Frequently Asked Questions
Before you choose technology
Uses, integration and costs for LangChain.
01 / Match
When that choice makes sense
What projects do you consider LangChain for?
Suitable situations: AI assistants; RAG; Document automation; Toolflow. The choice shall be confirmed after analysis of existing requirements, team and solutions.
What uses do you propose for LangChain?
Relevant examples are: AI Chains; Document Connection; Tool Calling; Prototypes AI. We determine what serves your objective and what would add complexity without a clear benefit.
02 / Implementation
Integration and deliverables
Can the solution be integrated into an existing project?
We define approved sources, access to data and permitted actions. We start with a limited flow, with human verification for important results or operations.
What could include implementation?
For LangChain, we can define in the offer: AI Flow Architecture; Model Connection; Rules and Validation; Logs; Scenario Testing. We confirm the deliverables after verification of compatibility and available access.
03 / Operation
Verification and costs
How do you check that implementation works?
We assess the results on representative examples and difficult cases. We check correctness, permissions, errors and cost; where answers are generated, we also assess loyalty to sources.
What costs should be foreseen in the long term?
We design data preparation, integration, subscriptions or use of APIs and monitoring. The estimate shall be based on a test volume and shall include agreed consumption limits.