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Services · AI agent consultancy

Six delivery tracks that take agents past the pilot

We design, build, and deploy custom multi-agent systems for healthcare, semiconductor, predictive maintenance, process automation, and document operations — with the integration, evaluation, and governance a pilot needs to become a production system your team owns.

Why Operations Teams Engage Us

Built for operations and technology leaders accountable for speed, cost, and quality
Full lifecycle — diagnosis, architecture, build, integration, and post-launch operation
Governance designed in from the first workshop: control mapping, evaluation, and audit evidence
01Service Tracks

Consulting and Delivery Services

Six service lines covering the full AI agent lifecycle from strategic diagnosis to scaled operations.

▸ HOW TRACKS COMBINE

Tracks are normally combined, not bought separately. A first production workflow typically runs Strategy → Architecture → Development → Integration in 12-20 weeks. Ranges below are per track and are confirmed as a single fixed-scope proposal after discovery.

01 / 06

Agent Strategy & Consulting

Every engagement opens with an assessment of your AI readiness, data maturity, and operational landscape — so leadership can decide before a single line of code is written.

What You Receive

Written readiness and data-maturity report
Prioritized opportunity backlog, effort/impact scored
Editable ROI model with auditable assumptions
Target agent architecture recommendation
90-day roadmap with named owners and milestones
Timeline
2-4 weeks
Investment
$5K - $15K
02 / 06

Multi-Agent Architecture Design

A multi-agent system is more than wired-together LLMs. We define each agent's role, communication protocol, escalation path, and failure behaviour before anything is built.

What You Receive

Agent topology diagram with role definitions
Escalation and human-in-the-loop specification
Inter-agent communication and protocol maps
Failure-mode and graceful-degradation plan
Build-ready technical specification
Timeline
3-6 weeks
Investment
$10K - $30K
03 / 06

Custom Agent Development

We build production-grade agents on frontier and open-weight models, equipped with tool use, persistent memory, and reasoning chains tailored to your domain.

What You Receive

Working agents running in your environment
Evaluation suite with a recorded baseline
All source code committed to your repository
Weekly demo builds and written feedback loops
Operator runbook for the team who inherits it
Timeline
6-12 weeks
Investment
$25K - $75K
04 / 06

Enterprise Integration

Agents create value only inside your existing workflows. We integrate with CRM, ERP, HRIS, and custom platforms through a phased cutover, so existing processes keep running during rollout.

What You Receive

Documented API contracts for every integration point
SSO and RBAC configuration in your identity provider
Data transformation and reconciliation pipelines
Failure runbook — retries, circuit breakers, escalation
UAT pack your operations team signs off against
Timeline
4-8 weeks
Investment
$15K - $50K
05 / 06

Agent Monitoring & Optimization

After deployment we instrument every agent — latency, token usage, cost per interaction, accuracy, and satisfaction signals flow into dashboards your team controls.

What You Receive

Live cost, latency, and accuracy dashboard
Monthly optimization report with tracked deltas
A/B test design and written results
Alert thresholds for regression and drift
Quarterly cost review with reduction options
Timeline
Ongoing
Investment
$5K - $15K/month
06 / 06

Agent Security & Compliance

AI agents introduce novel attack surfaces — prompt injection, data exfiltration via tool calls, and PII disclosure — which we harden with defense-in-depth design.

What You Receive

Agent-specific threat model and trust boundaries
Control-mapping matrix (EU AI Act, GDPR, HIPAA, SOC 2)
Red-team findings with a remediation plan
CI-integrated vulnerability scanning configuration
Audit-ready design and evidence pack
Timeline
3-5 weeks
Investment
$10K - $25K
03Methodology

How we execute AI programs

A five-phase operating model built for enterprise delivery teams and measurable outcomes.

01

Discovery & Assessment

DELIVERABLE · Prioritized roadmap

We immerse ourselves in your operations, data infrastructure, and strategic objectives. Through stakeholder interviews, process mapping, and data audits, we identify the highest-impact opportunities for AI agents and build a business case your leadership team can act on.

02

Architecture & Design

DELIVERABLE · Technical spec

Our architects design the agent topology, tool chain, memory systems, and integration points. Every design decision is documented with trade-off analysis. You receive interaction diagrams, data flow specifications, and a deployment plan before development begins.

03

Development & Testing

DELIVERABLE · Tested agents

We build iteratively in weekly sprints with live demos and feedback loops. Each agent undergoes unit testing, integration testing, and adversarial red-teaming. We validate against real-world scenarios from your domain before moving to staging.

04

Deployment & Integration

DELIVERABLE · Live production

Production rollouts run as canary or blue-green releases with a documented rollback path. We wire agents into your existing systems, configure monitoring, and validate end-to-end flows with your operations team before traffic shifts.

05

Monitoring & Optimization

DELIVERABLE · Ongoing tuning

Post-launch, we instrument dashboards for cost, latency, accuracy, and user satisfaction. Our optimization cycles run automated A/B tests, refine prompts, and surface cost reduction opportunities — keeping your agents sharp as your business evolves.

▸ NEXT STEP

Not sure which phase you are in?

Most teams start with a 2-4 week diagnostic. We will tell you in the first call if you do not need one.

Request a strategy call
04Engineering Stack

The stack we build agents on

Vendor-agnostic by design — we select the right model, framework, and infrastructure for your data, latency, and compliance constraints.

LLM Providers07

Frontier + open-weight · cloud or on-premise

Anthropic
OpenAI
Gemini
Llama
Mistral
Ollama
Hugging Face
Agent Frameworks06

Planning, tool use, orchestration

Claude Agent SDK
LangGraph
LangChain
CrewAI
Pydantic AI
LlamaIndex
Retrieval & Vector06

RAG, embeddings, hybrid search

Pinecone
Milvus
pgvector
Elasticsearch
OpenSearch
Redis
Cloud & Deployment08

Public cloud, on-premise, air-gapped

AWS
Azure
Google Cloud
On-premise
Docker
Kubernetes
NVIDIA
Terraform
Data & Streaming06

Pipelines, warehouses, event streams

PostgreSQL
Snowflake
Databricks
Kafka
Airflow
ClickHouse
Languages & Runtime05

Production services + tooling

Python
TypeScript
Rust
FastAPI
Node.js
Observability & Eval06

Tracing, metrics, evaluation, guardrails

OpenTelemetry
LangSmith
Grafana
Prometheus
MLflow
Sentry
▸ VENDOR POSTURE

We are model- and vendor-agnostic. Every component is chosen against your workflow complexity, data residency, latency budget, and compliance obligations — including EU AI Act, HIPAA, and SOC 2 — and runs equally in cloud or air-gapped on-premise environments.

Product names and marks shown are the property of their respective owners and indicate technologies we build with — not partnerships or endorsements.

05Get Started

Get an AI Operations Service Plan

In one strategy session, we will map priority workflows, define service scope, and recommend the fastest path to measurable impact.

No commitment required · Response within one business day

▸ ENGAGEMENT SNAPSHOT
First response
One business day
Diagnostic engagement
2-4 weeks
First production workflow
12-20 weeks
Code and IP ownership
Yours