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AI Agents Development

Agents that,
actually finish the task.

We design, build and deploy multi-step AI agents — tool-using, self-correcting, human-in-the-loop where it matters. Senior engineers, sprint-based delivery, measurable task completion.

4.9/5 · 180+ teams shipping with our engineers · NDA on request

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Multi-Agent
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Zia · AI Agent Expert

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— What We Do

Six agent patterns, one delivery team.

From single-tool assistants to fully autonomous multi-agent systems, we ship the pattern that fits the job — never the other way round.

Agents that,
take action, not just suggest.

Multi-step agents that plan, call your tools (CRM, ERP, ticketing, payments), self-correct on failure, and close the loop — with human-in-the-loop guardrails and full traceability.

Tool use

Planning + reflection

Memory & state

Eval harness

Human handoff

1

PLAN

Decompose the goal into steps

2

ACT

Call tools, APIs, and systems

3

VERIFY

Self-check, escalate, or retry

Outcome

↑ 4.6x tasks closed without human intervention ↓ 41% average handling time

14 years · 290+ bots

Built to,
finish the task, not draft a reply.

21+

Agent systems shipped

across 9 industries

14yrs

Years in business

founded 2012

95%

Engagement extension

clients renew or expand

<2wk

Kickoff time

brief → first standup

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Capabilities & stack

Boring orchestration that
completes tasks on time.

We pick the agent framework and model for the job, not the trend. Closed-source where reasoning quality matters most, open-source where you need control. Always evaluated, never vendor-locked.

How we pick

01

Eval before autonomy

Every agent run through a task-specific harness before it gets write-access to any tool.

02

Cost & latency budgeted

Per-task and per-tool-call cost captured upfront so autonomy doesn’t mean runaway spend.

03

Swap-ready orchestration

Framework-agnostic core so you can switch models or tools without a rewrite.

04

Guardrails by default

Scoped tool permissions, approval gates, and rollback baked into every agent.

LANGUAGE MODELS

GPT-4o

GPT-4.1

Claude Sonnet 4.5

Claude Opus 4

Gemini 2.5 Pro

Llama 3.1 / 3.3

Mistral Large

DeepSeek-V3

Qwen 2.5

Phi-4

AGENT FRAMEWORKS

LangGraph

CrewAI

AutoGen OpenAI Agents SDK

Semantic Kernel Pydantic AI

Vercel AI SDK

DSPy

TOOL USE & INTEGRATIONS

Model Context Protocol (MCP)

Zapier Custom function-calling APIs CRM/ERP connectors

Webhooks

OBSERVABILITY & EVAL

LangSmith

Langfuse

Helicone

Braintrust

Ragas

TruLens

OpenLLMetry

PromptLayer

Voice & omnichannel

Twilio

Vonage

Deepgram

ElevenLabs

Whisper

WhatsApp Cloud

Slack

Teams

Intercom

Zendesk

Industries

Agents, tuned for
your industry.

Every industry has its own systems, edge cases and escalation rules. We bring domain playbooks, not blank slates — and wire agents into your data and tools on day one.

01 · Industry

Healthcare

Prior-authorization and claims-processing agents

02 · Industry

Finance & Fintech

Dispute-resolution and chargeback agents

03 · Industry

Retail & E-commerce

Order-management and return-processing agents

04 · Industry

Logistics

Exception-handling and re-routing agents

Engagement models

Pick how you want to
ship agents with us.

Three ways to engage — all senior teams, all sprint-based, all measured against the task-completion outcomes we agree on before kickoff.

Fixed-scope

 Workflow Audit

Best for teams unsure which workflows to automate first.

Fixed-scope

Fixed-Scope Build

Best for a specific agent with a clear brief.

Embedded

Staff Augmentation

Plug in vetted AI engineers into your team.

FAQ

The questions
everyone asks before kickoff.

Still curious? Ask Zia in the hero chat — or book a 30-min strategy call with a senior AI engineer.

Do you build with closed models (GPT, Claude) or open-source?

Both — we pick per agent based on reasoning quality needed, latency, and cost. Closed models (GPT-4o, Claude) often win for complex planning steps; open-source (Llama, Qwen) works well for high-volume, simpler tool calls where cost matters more. We benchmark before recommending.

Every agent runs inside scoped tool permissions, so it can only call what it’s explicitly allowed to. High-stakes or ambiguous steps route through human-approval gates, and every action is logged for audit and rollback.

Yes — we integrate directly with your CRM, ERP, ticketing system, or internal APIs via function calling or MCP, with proper auth scoping. We audit access requirements during the workflow audit before any build starts.

It escalates to a human with full context — what it tried, what failed, and why — instead of guessing or looping. This handoff logic is built into every agent by default, not bolted on later.

We define task-completion rate, escalation rate, and cost-per-task upfront, then track them through a dedicated eval harness before and after launch — so you see real numbers, not anecdotes.

Every tool call, decision, and escalation is logged for full auditability. For regulated industries (healthcare, finance) we align agent permissions and data handling to HIPAA/SOC2 requirements from day one.

Yes — the reasoning core is channel-agnostic, so the same agent can operate over voice (Twilio/Vonage), WhatsApp, Slack, or Teams without rebuilding logic per channel.

Cost depends on agent complexity, number of tools, and volume of tasks — simple single-tool agents cost far less than multi-agent orchestration. We share a fixed-price estimate after the workflow audit, with no surprise billing.

Healthcare · HIPAA-ready since 2012

Let's build a agent worth trusting.

Send your brief — a senior AI engineer (not a sales rep) replies within 24 hours with a scoped plan, tool/model recommendation and a fixed timeline.

What you’ll get