LangChain Consulting & Development
AI agents that investigate broadly and write narrowly
LangChain is our framework of choice when an agent needs tools, retrieval, and room to work out what a request actually means: document and email intake, order and exception handling, and multi-step internal copilots. This page complements our broader AI agent development services.
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What We Build with LangChain
Agent and Tool Architecture
We design the agent and the tool layer it calls: what the agent is allowed to read, what it is allowed to write, and what it must escalate. Every tool is scoped, validated, and logged, so an agent can investigate broadly while writing narrowly.
Document and Email Intelligence
We build LangChain agents that read the unstructured inputs your business actually receives: PDFs, spreadsheets, scans, email threads, and follow-up replies. The agent classifies intent and extracts structured fields from formats that vary by sender.
Supervisor and Subagent Patterns
For work that splits into independent tasks, we build a supervisor that decomposes and routes, and focused subagents that each investigate one bounded action and report back. Narrow remits make agent behaviour reviewable.
Controlled Write Paths
Agents recommend; validated tools execute. We build the write gate that checks required fields, duplicates, and payload structure against your system of record before anything is created or edited, and escalates to a human when it cannot.
Retrieval on Governed Data
We ground agents on your warehouse, your ERP, and your documented business rules rather than a generic vector store. Retrieval quality is a data engineering problem before it is a prompting problem.
Model Routing Across Providers
We use OpenAI, Anthropic Claude, Google Gemini, and smaller open-source models as the right choice per step. Reasoning-heavy steps get a frontier model. Routine extraction gets a cheaper, faster one.
Technical whitepaper
A CIO guide to trusted analytics interfaces for AI agents
This companion whitepaper is written for CIOs, CTOs, and data leaders evaluating AI-agent workflows that touch revenue, billing, operations, manufacturing, and supply chain decisions. It explains why connecting an assistant to business applications is not enough, and how to expose governed analytics answers.
Designing MCP Servers for Business Analytics
A practical whitepaper for leaders designing agent-ready analytics interfaces, including concrete examples for:
- Retail & E-commerce Analytics
- Manufacturing Data Analytics
- Logistics & Supply Chain Analytics
PDF format, free to download.
When LangChain Is the Right Choice
- The inputs to a business process arrive as language: emails, PDFs, spreadsheets, and replies that no two senders format the same way.
- A team spends its day reading documents and re-typing the contents into a system of record.
- You want automation, but a wrong write into your ERP or WMS is more expensive than no automation at all.
- The easy cases are genuinely easy and the hard cases genuinely need a person, and today both take the same amount of manual effort.
- You need every automated decision to be traceable: what the agent read, what it concluded, what it changed, and who approved it.
Why Choose Witanalytica for LangChain
We Pick the Pattern, Not the Hype
LangChain fits when an agent needs tools, retrieval, and room to investigate. When the workflow is a predefined state machine that must pause and resume, we reach for LangGraph. When the work is simple, we use normal code. We do not force every workflow into one tool.
Bounded Autonomy by Design
Agents investigate; deterministic rules and validated tools decide what is allowed to execute. Adding autonomy and adding guardrails is the same design decision, not competing ones.
Grounded in Real Data
We come from years of BigQuery, Snowflake, and BI engagements. Agent tools call governed data with tenant boundaries and audit trails, not random embeddings.
Cost-Aware by Default
We route steps to the cheapest model that does the job, cache tool calls, and surface costs in dashboards. Production AI does not have to be expensive.
Our LangChain Delivery Process
We map the work the agent will take on and, just as importantly, where its authority stops. We separate language interpretation from business authorization before any code is written.
We define and build the tools the agent calls: data queries, system lookups, notifications. Read-only first, with write tools introduced behind validation and explicit human approval.
We implement the agent, its prompts, its tool contracts, and its escalation paths, with structured logging on every tool call and model response so behaviour is traceable.
We run the agent on real data with all writes intercepted for review. We tune prompts, tools, thresholds, and escalation rules until quality and reliability are consistent.
We deploy to Cloud Run, Cloud Functions, or your own infrastructure, with structured logging, alerting, exception tracking, and cost dashboards wired in from day one.
We track success rates, escalation rates, latency, and model spend. Exceptions are a data source: every escalated case tells you where the next rule or tool belongs.
We map the work the agent will take on and, just as importantly, where its authority stops. We separate language interpretation from business authorization before any code is written.
TESTIMONIALS
Witanalytica has been an awesome team to work with. They have such a talented team with a broad range of expertise in software development, BI and data analysis - which have all been instrumental in helping us achieve our technical goals. We truly value their partnership and look forward to continuing to work together.
Gregg Bansavage
CIO, RBW Logistics
Witanalytica has been an excellent partner in managing and optimizing our Tableau environment. Their team’s technical expertise and proactive support have streamlined our reporting processes, improved dashboard performance, and provided valuable insights to our business. Their responsiveness and deep understanding of data analytics make them a trusted extension of our own team.
Mark Lack
Director of Data Analytics and AI, The Ubique Group
Witanalytica helped us transition from Excel to a dynamic dashboard, allowing us to view all the relevant data and the KPIs that we track as a business. Instead of having our developers code an interface for weeks, we can now instantly accomplish this process through an interface, eliminating the need for manual coding.
Radu Albastroiu
Startup Founder, masinilacheie.ro
Witanalytica’s expertise in big data engineering and visualization complements our digital media audit and customer analytics services. Collaborating with them allows us to deliver end-to-end analytics solutions and services, without the risks and investments associated with building these capabilities in-house.
Silviu Toma
Senior Partner, Microanalytics
Working with Witanalytica has transformed our approach to reporting. Their expertise in PowerBI enabled us to go beyond the limited capabilities of Excel, allowing us to provide our clients with dynamic and visually captivating PowerBI dashboards. This capability has facilitated rapid testing, iteration, and the collection of customer feedback to improve our platform.
Alin Rosca
Startup Founder, RepsMate
Working with Witanalytica has been a consistently positive experience. They are responsive, professional, and approach every revision with patience and precision. What sets them apart is a strong understanding of supply chain management, inventory planning, and sales operations, which makes collaboration efficient and ensures deliverables align with real business needs. They have also worked effectively across multiple departments in our organization and manage a 6-7 hour time zone difference seamlessly. I would confidently recommend them to any organization seeking a skilled and dependable analytics partner.
Rubin Chen
Supply Chain VP, The Ubique Group
Our LangChain Consulting Pricing Models
Transparent pricing built for long-term partnerships, not one-off transactions.
On-Demand Expertise
All tasks are tracked, and the corresponding invoice of the delivered services is billed monthly.
| Activity | Hourly Rate |
|---|---|
| AI Agents Development and Implementation | $100 |
| Data Engineering & Database Administration | $110 |
| Business Intelligence Reporting | $90 |
| Data Science | $120 |
Reserved Capacity Agreement
- Pre-purchase a package of monthly working hours that guarantees reserved capacity and priority availability, regardless of our workload.
- Because this capacity is exclusively allocated to you, unused hours do not carry over to the following month.
| Hours Package | Price |
|---|---|
| Every 50 hours | $4,500 10% savings |
Alternatively, we also offer project-based pricing
For well-defined engagements, we scope the full project upfront and agree on a fixed fee, so you know exactly what to expect.
Your Goals, Our Expertise
We start from your strategic objectives and work our way back to the right mix of solutions and technologies, not the other way round.
Book a Consulting CallRelated Insights
How we think about agent frameworks, guardrails, and production readiness.
4 articles
AI Agent Frameworks for Lean IT Teams: How to Choose What You Can Actually Operate
How lean IT teams should evaluate AI agent frameworks by what they can deploy, observe, approve, and maintain in production.
Why AI Agents Still Get Business Questions Wrong
MCP and APIs can connect Claude to business apps, but they do not guarantee trusted answers. Learn why AI agents still need governed business definitions.
LangGraph vs OpenClaw: How to Choose Between Predictable Automation and Autonomous Agents
Read along to understand when LangGraph is safer, and when OpenClaw's autonomy is worth the risk.
LLMs for Data Analytics: Extracting Business Insights with AI
LLMs do more than generate text. See how they integrate with analytics workflows to surface patterns, automate reporting, and speed up decision-making.
Frequently Asked Questions
LangChain is a framework for building applications and agents on top of large language models. It provides the plumbing for tool calling, retrieval, memory, and model abstraction, so an agent can read data, call your systems, and act on the results rather than only answering questions.
They are part of the same ecosystem and solve adjacent problems. LangChain gives you agents, tools, and retrieval: the agent decides which tool to call next. LangGraph is lower-level orchestration that models a workflow as an explicit graph of nodes and edges with durable state, built for workflows that must pause for approval, resume later, and be audited step by step. LangChain suits agentic investigation; LangGraph suits predefined, audit-heavy processes. Many production systems use both.
When the agent needs to do more than answer: look data up in your systems, read attachments, check a record, and then act. A single LLM call is fine for one-shot text tasks. LangChain is the right tool when the model needs tools and context to complete real work.
By never letting the agent write directly. Agents investigate and recommend; a separate validated tool performs the write only after deterministic rule checks pass: required fields, duplicates, entity resolution, and payload structure. If any check fails or the case is ambiguous, the work escalates to a person with the evidence already gathered. In production, this is the difference between an exception and an error.
No. LangChain is model-agnostic. We routinely mix OpenAI, Anthropic Claude, Google Gemini, and smaller open-source models in the same system, picking per step based on the task and cost.
Every tool invocation, model response, and decision is logged. We integrate LangSmith or your existing observability stack, and we persist both successful runs and exceptions to your warehouse so operations can track automation value and failure patterns in the same place.
A focused agent with a handful of tools, grounded on existing data, typically goes from discovery to a supervised production pilot in 4 to 6 weeks.
We offer two engagement models with transparent pricing.
On-Demand Expertise
All work is tracked and billed monthly at hourly rates:
- AI Agents Development and Implementation - $100/hr
- Data Engineering & Database Administration - $110/hr
- Business Intelligence Reporting - $90/hr
- Data Science - $120/hr
Reserved Capacity Agreement
- Pre-purchase a 50-hour monthly package at $4,500 (10% savings)
- Guaranteed priority availability regardless of our workload
We also offer project-based pricing for well-defined engagements.
Contact us to discuss the best fit for your needs.