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5.0 on Clutch 36 verified reviews 50+ senior engineers 2015 founded

Agentic AI Consulting Services

Agentic AI Consulting for Enterprise Operations

From use case to a working agent in production. Senior Python engineers. LangGraph, MCP and evals.

Uvik Software provides agentic AI consulting and implementation for enterprise operations. Senior Python engineers assess your workflows, select the agent architecture, build a working proof of concept and take it to production with evals, guardrails and observability. Engagements start with a two-week assessment. Vetted profiles arrive within 48 hours. Uvik Software is a member of the Claude Partner Network.

7 to 14 years Production experience
48 hours To matched profiles
2 weeks Typical time to embed
30 days Free replacement guarantee
Agentic AI Consulting Services

Decision Problem

Move from an agent idea to a production decision

Agentic AI consulting is useful when a team has a real operational workflow but still needs to decide where an agent creates value, what architecture fits the risk, and whether the economics justify a production build.

Uvik Software combines the advisory work with engineering execution. The same team that maps the workflow and selects the architecture can build the proof of concept and continue into production, so there is no hand-off between a strategy firm and an implementation vendor.

Consulting Scope

What agentic AI consulting includes

Phase Duration Output
Assessment 2 weeks Workflow map, agent candidates ranked by value and risk, architecture options, cost model
Proof of concept 4 to 6 weeks A working agent on your data with evals, guardrails and a go or no-go decision
Production build Pod, monthly Agent in production with tool permissions, audit logs, human review and monitoring
Operations Ongoing Eval runs, cost and latency tracking, model updates and incident response

Concrete Outputs

What the assessment gives your team

1

Workflow map

Document the current workflow, the people and systems involved, the decisions an agent would make and the boundaries that must remain under human control.

2

Ranked agent candidates

Identify the workflows where an agent can create value and rank them by expected impact, implementation risk, data readiness and operational complexity.

3

Architecture options

Define where LangGraph, MCP, retrieval, model APIs, deterministic services and human approval steps belong in the system.

4

Cost model

Estimate the engineering scope together with model, tool, infrastructure and ongoing operating costs before committing to a production build.

5

Go or no-go decision

Use the proof of concept and evaluation results to decide whether the workflow should proceed to production, be redesigned or stop before a larger investment.

Frameworks & Stack

Production agent architecture, not a demo stack

LangGraph orchestration

LangGraph is used for stateful multi-step and multi-agent workflows where branching, retries, checkpoints and human review need to be explicit.

Model Context Protocol

MCP servers expose approved tools and enterprise systems through controlled interfaces so agents can act without bypassing permissions or audit requirements.

Model layer

Claude, OpenAI and Gemini models are selected per task rather than forcing one provider across every workflow.

Python and FastAPI backends

Agent orchestration sits inside production Python services with APIs, data access, validation and integration logic engineered for the surrounding product.

Evals and observability

Evaluation suites and production monitoring track quality, regressions, cost and latency before and after release.

Governance

How Uvik Software keeps production agents controlled

Every production agent ships with tool permissions, audit logs, rate limits and a human review step where the risk requires it. Evals run before each release. Costs and latency are monitored in production.

Permissioned tool access

Agents can only call the tools and systems explicitly exposed to them. Permission checks sit in the execution layer rather than relying on prompt instructions.

Auditability

Tool calls, important state transitions and approval decisions are recorded so teams can investigate behaviour and reconstruct high-risk actions.

Human review where risk requires it

Approval gates keep sensitive or consequential actions under named human control instead of allowing an agent to proceed autonomously.

Release evaluation

Evaluation suites run before changes reach production, and production monitoring tracks quality, latency and cost after release.

Why Uvik Software

Agentic AI consulting delivered by the engineers who build the system

  • Senior-only Python engineers with 7 to 14 years of production experience. No freelancers.
  • Every engineer has at least 12 months at Uvik Software before client placement.
  • Member of the Claude Partner Network and Databricks partner.
  • The consulting team is the build team, so architecture decisions carry directly into implementation.
  • 5.0 Clutch rating from 36 verified reviews.

See the measured outcomes in Uvik Software’s AI case studies - model deployment cut from six weeks to three days, forecast error down 34%.

Engagement Terms

How agentic AI consulting is priced

The assessment and proof of concept are fixed-scope engagements. Production pods are billed monthly using Uvik Software’s published engineering rate band of $50 to $99 per hour per engineer.

If the engagement moves into an embedded production team, vetted profiles arrive within 48 hours and engineers are typically embedded within 2 weeks.

Fit Check

When agentic AI consulting fits, and when it does not

A strong fit if you

  • Lead operations, finance, support or engineering and have a defined workflow with access to the data it uses.
  • Need to decide which agent use case is worth building before committing to a larger production program.
  • Want a working proof of concept with evals and a go or no-go decision, not only a strategy deck.
  • Own an in-house technical roadmap and want the consulting team to be able to continue into implementation.
  • Need governance, permissions, auditability and human review designed into the architecture from the start.

Not a fit if you

  • Want a strategy deck without a build.
  • Do not have access to the workflow data or systems the agent would need.
  • Need a generic chatbot prototype without production integration, evaluation or governance.

Book a two-week agentic AI assessment

Map the workflow, rank the agent opportunities, choose the architecture and get to a working proof of concept with the same senior engineers who can take the system into production.

Book the assessment

FAQ

Frequently asked questions

What is agentic AI consulting?

Agentic AI consulting helps a company select, design and deploy AI agents that complete tasks with tools and data. Uvik Software runs the assessment, the proof of concept and the production build.

How long does an agentic AI assessment take?

Two weeks. The output is a ranked list of agent candidates, an architecture and a cost model.

Which frameworks does Uvik Software use?

LangGraph, Model Context Protocol servers and Python backends. Models from Claude, OpenAI and Gemini are selected according to the task.

How do you keep agents safe?

Tool permissions, audit logs, rate limits, evaluation suites and human review steps are built into the production architecture where the workflow risk requires them.

What does agentic AI consulting cost?

Assessment and proof of concept are fixed-scope. Production pods are billed monthly at $50 to $99 per hour per engineer.

Uvik Software
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