SLED Subcontracting
AI Productivity

Turn team knowledge into instant answers

Techtiz builds internal AI assistants that answer from your Slack and documents via hybrid search, plus productivity tools that unify chat, scheduling, and document work in one place.

Scope a knowledge assistant build See what we build
Hybrid search + reranking Built on your own data RAG, not a generic chatbot
AskTiz · retrieval pipeline
RAG + reranking retrieval architecture we ship
Source Slack conversation history
Index pgvector semantic embeddings
Answer Hybrid search, reranked
Where it pays back
  1. Workflow · 01

    Institutional knowledge lives in Slack, nowhere else

    A decision made six months ago is buried in a thread nobody can find.

    A Slack-native assistant that ingests history and answers in plain language

  2. Workflow · 02

    Employees re-derive answers that already exist

    The same question gets asked and re-researched every quarter because nobody can retrieve the original context.

    Semantic search over your own conversations, with reranked results

  3. Workflow · 03

    Productivity work is scattered across disconnected apps

    Chat, calendar, and document creation live in separate tools, so context gets lost switching between them.

    One assistant surface for chat, scheduling, and document work

Integration reality
Slack and collaboration platforms Vector databases (pgvector) Calendar and scheduling APIs Document stores
Capabilities

AI consulting and readiness

A build decision in 2 weeks, not a slide deck.

Audit · Use-case scoring · Roadmap

2 weeks, fixed scope Explore AI readiness

Agentic engineering

Agents with evaluations, approval gates, cost ceilings, and a full audit trail.

RAG · Tool use · Voice · Governance

6 to 8 weeks to production Explore agentic engineering

Forward deployed engineering

A named senior engineer inside your team, owning an outcome.

Embedded · Weekly demo · Named lead

Monthly, 30-day exit Explore forward deployed engineering

Custom software, web and mobile

Specification first, AI-assisted, senior review on every merge.

Next.js · NestJS · Flutter · React Native

Scoped per build Explore custom software

Automation and systems

Workflows wired and instrumented, with the payback counted.

n8n · Make · CRM · Back office

Monthly retainer Explore automation

Data and platform

Pipelines and lineage your AI can actually rely on.

Warehouse · ETL · Lineage · Observability

Audit, then phased Explore data & platform
Case studies
All case studies →
AI Automation

AskTiz – Internal AI Knowledge Assistant for Slack

Problem AskTiz turns an organization's Slack workspace into a searchable knowledge
Approach Real-time Slack ingestion pipelines using the Slack Events API and an
Relevance Turned scattered Slack history into a searchable institutional memory
FAQ

Does the assistant answer from our own data, or a generic model?

Your data. We ingest your conversations and documents into a retrieval index, so answers are grounded in what your team actually said and wrote.

What is hybrid search with reranking?

Semantic (meaning-based) search combined with keyword matching, then a reranking pass over the results so the most relevant answer surfaces first, not just the closest embedding.

Where does our conversation data live?

Your environment or a dedicated tenant, mapped in writing before anything is built.

Start the conversation

Stop losing decisions to a Slack thread nobody can find

Tell us where your team wastes time re-deriving context that already exists. We will tell you what a retrieval build looks like on your own data.

Scope a knowledge assistant build